Sandra Câmara Olim

Valentina Nisi

Augmented Reality towards facilitating abstract concepts learning

Keywords: Augmented Reality, Edutainment, Non-formal learning, Periodic Table

 Elements in non-formal settings. After designing and implementing the game, we conducted an exploratory study with 36 young participants, using a mixed-method approach. A comparative study between pre-and post-intervention questionnaires and observation results shows a positive learning outcome, demonstrating the potential of this tool in a non-formal context.

Introduction

The acquisition and development of abstract reasoning is extremely important in children's. Great part of abstract reasoning acquisition happens during the learning process of school subjects. These subjects, involve inquiry, experimentation, evidence, the evaluation and analysis of ideas, problem-solving, creative thinking, and overall understanding of information by making connections with the real world [START_REF] Squire | Mad city mystery: Developing scientific argumentation skills with a place-based augmented reality game on handheld computers[END_REF]. Children's understanding of abstract concepts in STEM disciplines has been shown to increment by means of spatial reasoning [START_REF] Newcombe | Early education for spatial intelligence: Why, what, and how[END_REF] enabling them to reason about the space around while manipulating real or imaginary object configurations in space [START_REF] Buckley | A heuristic framework of spatial ability: A review and synthesis of spatial factor literature to support its translation into stem education[END_REF].

Playful educational experiences and games have shown positive effects in a wide spectrum of the development of cognitive skills [START_REF] Host'oveckỳ | Serious game in science education: How we can develop mathematical education[END_REF][START_REF] Fissler | Educational games for brain health: revealing their unexplored potential through a neurocognitive approach[END_REF]. Educational games increase concentration levels and stimulate learning in children [START_REF] Arcos | Playful and interactive environment-based augmented reality to stimulate learning of children[END_REF], allowing for the exploration of teaching tools such as metaphors, analogies, and the spatial manipulation of 3D objects through technologies like Virtual and Augmented Reality [START_REF] Shelton | Exploring a cognitive basis for learning spatial relationships with augmented reality[END_REF]. Virtual and Augmented Reality serious games create compelling, collaborative and participatory experiences to enhance the user's engagement and learning. These experiences can provide alternatives to a real-world environment for situated learning, allowing the user to experience a sense of "being there" while applying acquired knowledge [START_REF] Dede | Immersive interfaces for engagement and learning[END_REF]. Immersive games hold great potential for cognitive and motor development, and represent a powerful tool to facilitate the teaching of school curriculum and an effective way of acquiring knowledge within a non-formal context. Playing games is also considered a crucial activity for human development of socialization, expression, and communication skills [START_REF] Paredes | Juego, luego soy. Teoría de la actividad lúdica[END_REF]. Given these conditions, knowledge is acquired through a participatory process whereby the learner is "transformed through his actions and relations with the world" [START_REF] Britton | Vygotsky's contribution to pedagogical theory[END_REF]. As argued by John Dewey, teaching involves "engaging children in a fun and playful environment, imparting educational content, and instigating interest in learning more" [START_REF] Dewey | Liberalism and social action[END_REF].

Given the possibility of transporting knowledge to other settings, Augmented Reality enables the connection between content knowledge and user context, thus making the learning more effective. Many Augmented Reality games have proved especially effective for STEM subjects. AR enables users to visualize otherwise inaccessible representations and to experiment in a low-risk and lowcost platform [START_REF] Azuma | A survey of augmented reality[END_REF]. Augmented Reality has also been shown to be a powerful tool in the development of spatial skills, such as student understanding of structures that can be either invisible to the naked eye or spatially complex [START_REF] Wijdenes | Leveraging augmented reality training tool for medical education: A case study in central venous catheterization[END_REF][START_REF] Dunleavy | Augmented reality teaching and learning[END_REF][START_REF] Valimont | The effectiveness of augmented reality as a facilitator of information acquisition in aviation maintenance applications[END_REF].

The Periodic Table is one of the biggest achievements in the modern sciences, not only for chemistry, but also in physics, medicine, earth sciences and biology. In 2019, the United Nations celebrated the 150th international anniversary of the discovery of the Periodic System by Dmitri Mendeleev. As a result, numerous competitions, events and museum exhibitions have been dedicated to this topic. We took this opportunity to reflect on the Periodic Table and its elements and introduce them to young children, who might have not experienced them yet in their school curricula.

In this article, we present our research based on the design and preliminary testing results of Periodic Fable, a game intended to promote non-formal learning of the concepts of the Periodic Table for 11 years old and younger children, that have not tackled "chemistry" as a school subject yet. Periodic Fable incorporates image recognition, tangible objects, 3D virtual reconstruction of models, animations, and is part of a growing number of initiatives that seek to utilize this type of technology to create awareness and engage children in non-formal science learning. The project was designed and produced to complement the celebrations of the anniversary of the Periodic Table .  2 Related Work

Learning Framework

Situated learning builds upon social learning and development theories, according to which the quality of learning depends on social interaction with the learning context [START_REF] Roth | Authentic school science: Knowing and learning in open-inquiry science laboratories[END_REF][27] [START_REF] Vygotsky | Thought and language (e. hanfmann & g[END_REF]. Many virtual games and immersive simulations have been designed for training and education, to motivate students by providing a more immersive and engaging learning environment to support situated learning. The seamless integration of virtual content with the real environment can evoke in the users a perceptual state of non-mediation, a sense of presence reinforcing immersion [START_REF] Riva | Interacting with Presence: HCI and the Sense of Presence in Computer-mediated Environments[END_REF]. AR design strategies create virtual immersive experiences and games, which are based on action and symbolic and sensory factors. Research has shown that immersion in virtual environments can enhance education by allowing for multiple perspectives of the learning content, applying situated pedagogy and transfer of knowledge [START_REF] Dede | Immersive interfaces for engagement and learning[END_REF]. Even exceptional students in formal educational settings often find it difficult to apply what they learn in class to similar real-world contexts [START_REF] Dede | Immersive interfaces for engagement and learning[END_REF]. AR allows users to discern and interact with the real environment while simultaneously receiving additional digital information into their field of perception [START_REF] Bower | Augmented reality in education-cases, places and potentials[END_REF]. The simulation of real-world problems and contexts can be obtained by near transfer. This assimilation of knowledge can then be transferred to other situations, allowing for the construction of more knowledge. Examples of this process can be found in game simulations for flight and surgical training, whereby the user can practice and train certain skills, making mistakes and getting positive feedback when the task is performed in a low-risk environment before transferring this knowledge to real-world situations.

Children learn by using their senses, playing and performing activities, assimilating concepts in an intuitive manner [START_REF] Kritzenberger | Collaborative and constructive learning of elementary school children in experiental learning spaces along the virtuality continuum[END_REF]. Constructivism theory argues that children learn by interacting with the physical environment, socially, and by responding to external stimuli consciously. A constructivist environment allows children to build on previously acquired knowledge, in a reflexive process directed by a teacher, parent, or colleague [START_REF] Zurita | A constructivist mobile learning environment supported by a wireless handheld network[END_REF]. Likewise, learning by doing is a fundamental activity in children. It is successful when the information is comprehended and used, and this, in turn, contributes to a change, hence transformation in cognitive structure [START_REF] Gardner | Using multiple intelligences to improve negotiation theory and practice[END_REF]. The potential of Augmented Reality and educational games is supported by constructivism theories. Learning can also benefit from novelty effects due to new technologies [START_REF] Radu | Augmented reality in education: a meta-review and cross-media analysis[END_REF], since the excitement and curiosity of the students cause them to be more engaged and motivated.

Research shows that students' performance is affected in different variables of the learning process, while engaging in an activity individually or in a collaborative process. [START_REF] Arvanitis | A human factors study of technology acceptance of a prototype mobile augmented reality system for science education[END_REF]. Some effects are related to the intrinsic motivation (enjoying the activity itself), self-efficacy (believe in the capacity to solve a task) and self-determination (decision to do something). These results have been shown in many AR experiences where the activity is performed individually, but also studies shown that there is a tendency for active exchange of knowledge while students performed an AR activity [START_REF] Hung | Applying augmented reality to enhance learning: a study of different teaching materials[END_REF]. However limited of research is known about the learning efficacy when comparing both methods [START_REF] Martín-Sanjosé | Playful interaction for learning collaboratively and individually[END_REF].

Augmented Reality

Augmented Reality (AR) is defined as the perception of reality that has been enhanced through computer-generated inputs and other digital information [START_REF] Azuma | A survey of augmented reality[END_REF]. AR falls in the realms between a physical and a virtual reality spectrum, meaning that AR supplements reality, rather than completely replacing it. AR is demonstrating to hold great potential in the area of Edutainment (education and entertainment) [START_REF] Pérez-Sanagustín | Augmenting reality and formality of informal and non-formal settings to enhance blended learning[END_REF]. As a pedagogical tool, AR enables critical thinking and develops creativity [START_REF] Zünd | Augmented creativity: Bridging the real and virtual worlds to enhance creative play[END_REF]. The continuous investment in Augmented Reality has led to a proliferation of apps in the educational realm, with an increase in off-the-shelf wearable devices, like Curioscope [START_REF]Curiscope: Bring learning to life[END_REF], a marker-based t-shirt that allows children to visualize 3D models of human anatomy. Elements 4D, by DAQRI, created an app for chemistry designed to simulate how elements of the periodic table react in real life [START_REF]DAQRI: Elements 4d interactive blocks[END_REF]. Animal Alphabet uses AR Flashcards to learn letters. ZooKazam [START_REF] Llc | Zookazam magical animals[END_REF] and Bugs 3D [START_REF] Ttpm | Bugs 3d interactive boom[END_REF] aim to teach about animal species. Arloon Plants [START_REF] Tm | Arloon plants[END_REF] allows children to learn about the flora. Star Walk [START_REF] Vito Technology | Star walk -the sky at your fingertips[END_REF] AR app suppor ts learning about the stars, the solar system and the planets. MerchEdu allows students to explore and interact with STEM concepts using a tangible cube [START_REF] Mergelabs | Merge edu[END_REF]. Despite their usefulness, however, many of the commercial AR applications targeted at children have not been evaluated for their effectiveness in learning outcomes. In addition, Augmented Reality's ability to render objects that are hard to visualize using 3D Models (simulation), makes the understanding of abstract concepts more manageable. AR can enhance learning environments, engage, stimulate and motivate students [START_REF] Di Serio | Impact of an augmented reality system on students' motivation for a visual art course[END_REF][START_REF] Duh | Augmented reality learning: New learning paradigm in co-space[END_REF]. In scientific subjects, complex approaches are required for the students to envision concepts like micro and macro-worlds, and its assimilation remains a difficult and challenging process. Students make observations, collaborate with others, inquire, ask questions, investigate and interpret data when engaging with the AR system [START_REF] Dede | Immersive interfaces for engagement and learning[END_REF]. Chemistry in public schools with large size classes suffers from limited resources and time available, and, as a result, some students do not have the opportunity to conduct experiments. AR simulation helps to bridge this gap, contributing to the observation of some reactions on a one-to-one basis [START_REF] Edomwonyi-Otu | The challenge of effective teaching of chemistry: A case study[END_REF]. In Switzerland, an AR virtual chemistry laboratory was created for students to view and acquire atoms through a virtual drag-and drop technique. This platform allowed students to construct their own complex molecules, developing active learning skills [START_REF] Fjeld | Alternative tools for tangible interaction: A usability evaluation[END_REF]. Besides the allowance of inquirybased learning, using this system also helped students to be active in the learning process [START_REF] Cai | A case study of augmented reality simulation system application in a chemistry course[END_REF]. Low-achieving students benefit considerably by interacting with 3D models of micro-particles, better understanding the composition of substances [START_REF] Cai | A case study of augmented reality simulation system application in a chemistry course[END_REF]. The teaching of molecule formation, covalent bond and molecule structure using AR vs traditional methods such as a textbook, proved to be more effective in improving student performance [START_REF] Pasaréti | Augmented reality in education[END_REF]. StereoChem is a mobile Augmented Reality application used to help students understand stereochemistry, focusing on the study of stereoisomers (molecular formulas that differ in spatial orientation) to help in the perception of the 3D molecules [START_REF] Kl | Stereochem: Augmented reality 3d molecular model visualization app for teaching and learning stereochemistry[END_REF]. Augmented Chemistry allows students to obtain and understand information about the spatial relations between molecules by using the input of keyboards and tangible interaction. Augmented Chemistry represents the molecules in a 3D environment, providing multiple viewpoints and control of the interactions [START_REF] Singhal | Augmented chemistry: Interactive education system[END_REF].

Tangible Interfaces

The combination of tangible, physical interfaces with tridimensional virtual imagery allows children to play, engage, and have fun as they learn, facilitating the cognitive load [START_REF] Billinghurst | A survey of augmented reality[END_REF] in a natural and genuine way [START_REF] Cai | A case study of augmented reality simulation system application in a chemistry course[END_REF].

Tangible interfaces can ease the communication of abstract concepts. This is the case of Digital MiMs, computer enhanced building blocks that support learning in mathematics, probabilistic behavior and more. Another example is ProBoNo, a software and tangible hardware prototype developed for children from four to six years of age. PrBoNo allows children to navigate virtual worlds more playfully and engagingly. A study of this system concluded that the tangible interface facilitated the transfer of knowledge acquired in a digital environment to a situation in the real world [START_REF] Göttel | Probono: transferring knowledge of virtual environments to real world situations[END_REF].

However, regarding the benefits of tangible interactions for children, Horn et Al. [START_REF] Horn | Tangible interaction and learning: the case for a hybrid approach[END_REF], advocate for a hybrid approach (a single interactive system that consists of two or more equivalent interfaces). Teachers and learners can select the most appropriate interaction according to the task and needs of a specific situation [START_REF] Horn | Tangible interaction and learning: the case for a hybrid approach[END_REF]. Moreover, Ambient Wood, a large-scale learning activity targeting 11-12year-old children, aims to teach children about the nature of scientific inquiry by means of tangible discovery, reflection, and experimentation. A study of the system highlighted that, while tangibility per se is not enough to engage children in a task, it is crucial to have the appropriate tangible system [START_REF] Marshall | Conceptualising tangibles to support learning[END_REF].

Methods

System Design

Periodic Fable is a serious AR game for android mobile devices (with gyroscope, accelerometer and compass sensor), designed and produced to target 8 to 11year-old children that come into contact with chemistry for the first time. The game developed using ARCore, Autodesk Maya, Mudbox and Adobe Photoshop, provides basic concepts about chemical elements like their symbols, atomic numbers, atomic weight, reactions with other elements, and products that contain the element. It also allows users to obtain information by scanning markers, and joining elements(depicted as creatures) to create reactions. Thus, the learning process becomes fun, engaging the students [START_REF] Dede | Immersive interfaces for engagement and learning[END_REF].

Content The content of the game was selected with the help of a Ph.D. student (in a Chemical biology related area) and two Chemistry teachers. It takes into account the knowledge of chemistry that our target audience already acquired in science classes. Children from 8 to 11 learned some basic chemistry notions while learning about topics like pollution (carbon monoxide), blood components, the atmosphere, photosynthesis (carbon, oxygen), and the cycle of water (hydrogen, oxygen), to name some. It is not until later that chemistry becomes a curricular subject. The elements selected to feature in the Periodic Fable game are the most abundant in the environment, and have compelling reactions, which makes the students more curious, inspiring them to speculate about possible combinations. The Periodic Fable design relies upon constructivism as a learning method, allowing the children to explore and interact freely with the content, thus complementing their knowledge about the chemical elements. Moreover, to create a connection between the content and the real-world, we decided to include information that could be transferred to the everyday routine of the children.

Technology/Game Mechanics The AR game uses a marker-based system and tangible cubes as part of the mechanics. The camera of the mobile phone scans a pattern/image, recognizes it, and superimposes a digital image on the screen of the device (in our case, 3D models and animations, 2D images, video, text and audio). The criteria for the selection of the equipment is based on the children's ease of access to mobile devices, their portability, and affordability. Autodesk Maya, Adobe Photoshop, Adobe AfterEffects and Unity 3D were used for the development of the game.

We designed a tangible cube as a starting point. The child has to explore each facet of the cube to gain access to different information, which allows the user physical manipulation and exploration of spatial arrangement. The decision is the result of several iterations, heuristic evaluation and small sample testing to make playing the game easy, without need for supervision (almost intuitive). Few instructions are necessary, thus avoiding cognitive overload. The game features a cube per element, and each face of the cube expresses qualities and scientific facts about that element. At the moment we have developed five cubes, corresponding to oxygen, hydrogen, carbon and nitrogen, because they are the most important elements; their covalent bond combinations are responsible for most of the biological molecules on earth. We added chlorine to the list because, like the other elements, its properties and reactions can be the most interesting and engaging for the children. In the future, we hope to develop the experience for all the elements of the Periodic Table, allowing users to position each cube in the proper location, and to construct their own physical Periodic Table.

Aesthetics Each tangible cube is dedicated to one chemical element. All the facets of each cube (used as markers) are identified with text and a 2D image of the character holding an icon indicating the type of information that will be prompted (story/book, curiosities/ question mark, combination /silhouette of a group of characters, code name, habitat/building, information / letter "i").

The 3D characters were designed taking into consideration the properties of the elements that they represent. For example, oxygen is a highly reactive element, and capable of combining with other elements. Because of this, oxygen is depicted as a friendly creature, illustrated with the code name of the symbol it represents: "O". The atomic number reflects the creature's age, and the atomic mass is indicated as its weight (see Fig. 2 number 1). We created these analogies for each element as a way to facilitate retention of the information. The creature's aesthetics, from color to animation, are also keyed to properties of the element and provided with several iterations to create more empathy with the user. The colors assigned to each character reflect the Robert Corey, Linus Pauline and Walter Koltun coloring standard convention known as CPK color, used to distinguish the atoms of chemical elements in molecular models [START_REF] Helmenstine | Science notes -learn science do science[END_REF] . The color scheme is associated with some properties of the elements. For example, hydrogen, a colorless gas, is white; chlorine is green; carbon is either charcoal or graphite; nitrogen is blue, since it makes up most of the atmosphere and oxygen is associated with combustion; blood is red. The inspiration for the base shape of our 3D character is the ball-and-stick model of the molecular models, whereas the body of the characters is rounded like the spheres that represented the atoms, and the arms and legs are rods that can connect and create bonds with other elements. We designed glasses for each of the individual characters, and feet, hands, and other human features to animate and give each element a different personality, so that children can associate the creatures to the element's properties, empathize and engage with them. For example, the animation for hydrogen is a calm Zen creature that floats while meditating, thus portraying its low density the fact that it is essential for life (see Fig. 1). Story The concept of content-infused story games (CIS Games) builds on the fusion between games and stories to educate children [START_REF] Fails | Child's play: a comparison of desktop and physical interactive environments[END_REF]. Building upon this concept, a facet of the tangible cube is designed to identify with the element it represents holding a book. These animations feature in short, funny animation clips, turning into stories the outcome of joining two or more elements, and the reactions that this might trigger. For example, one of the stories dedicated to hydrogen presents the characters having fun in a water-park. Two hydrogens slide down a water toboggan and get stuck at the end of the ride. The oxygen that slides next is unable to stop hitting the two hydrogen creatures, and all turn into water. Chlorine is depicted as a superhero that saves his friend from a huge bacterium in a lab. Our aim is to make children learn and remember some of the chemical combination's outcomes and properties while having fun.

Game-play

The game starts with a short tutorial that guides the children in understanding the mechanics of the game: how to explore the faces of a tangible cube, gather the elements/characters, and use them to create reactions. The participant selects one of the cubes (this selection can be random) and scans one of the markers/images on each facet, generating/uploading the information linked to that particular pattern.

Facet 1 (Information) Triggers an animation of a 3D character representing a chemical element. It also provides information about the chemical symbol, including atomic mass, chemical name and atomic number(see Fig. 2 number 1).

Facet 2 (Habitat) Uploads an image of an apartment building divided according to the blocks of Periodic Table (atomic weight and arranged in horizontal rows/periods and vertical columns /groups). We decided to showcase the different characters in this blocks/apartment location creating an analogy (apartment building vs location of the element in the periodic table), so children will assimilate the lodging of the element in the Periodic Table (see Fig. 2

number 2).

Facet 3 (Curiosities) In this facet corresponding AR scenes, 3D models of products that have that element within their composition are visualised (see Fig. 2 left-number 3).For example, we depict oxygen as being a compound that can be found on a Pepsi drink, a cleaning product like Vanish (see Fig. 2 right -number 3). Our design took a situated learning approach, whereby children can create connections with the products in their surroundings and chemical elements.

Facet 4 (Stories) Capturing facet triggers short clip (less than one minute) dedicated to that particular element reaction with another elements (see Fig. 2 number 4) Facet 5 (Combinations) Capturing facet 5 allows the children to select and explore the reactions of different elements. We placed icons on the left side of the screen for the user to select and then explore several reactions (water, fertilizer, ammonia, fire, ozone, or to create a diamond) (see Fig. 2 number 5). Once the user clicks on the button, the application will indicate what type of creatures/elements are needed, and the user will be prompted to scan the corresponding cube with the camera of the mobile device (see Fig. 2 number 6).

If this activity is performed correctly, the interface notifies the child with a message congratulating him or her for the reaction just created (see Fig. 3 number 2) and showing the elements that were part of the reaction (Fig. 3 number 3). Then an animation of the reaction just created plays out (see Fig. 2 number 6).

Each element experience ends when the user has explored all the facets of the cube dedicated to that element, and captured its reactions. The experience can be repeated for the other cubes, until all cubes have been explored. Since no dependencies of content have been designed, each child can explore one, two, three, or all the cubes, always achieving full closure with each experience.

User Technology Access

Most of the students (32; 88.9%) had access to a mobile device prior to the study, but four (11.1%) did not. 15 participants (41.7%) had access to a mobile device less than a year ago. 11 participants (30.6%) had had access to a mobile device for more than a year, 7 (19.4%) had had access to a mobile device for over 2 years, and only four (8.3%) had no access to a mobile device. 12 participants (33.3%) knew or had heard about AR technologies, while five (13.9%) had already used AR. Only four students (11.1%) had previous knowledge of the Periodic Table.

User Study Protocol

Recruitment was done through a local school at Santa Cruz, Madeira. The experimenter contacted a teacher from the school Computer Science club, explained the project's objectives and demonstrated the study procedures. Parents signed Parental Consent before the intervention, which included information about the date and time of the study. On the intervention day, we briefed the participants and asked them to answer a pre-test questionnaire, which included questions like: What happens when you combine one oxygen and two hydrogen? What is the symbol for nitrogen? What formed the ozone? What products have chlorine in them? What are the elements found in diamonds? After having answered the questionnaire, the participants were assigned randomly to one of the two groups, to avoid any bias. Each group of participants experienced one condition. Group 1 (Control Condition) performed the intervention individually while, Group 2 (Experimental Condition) performed the intervention in pairs (see Fig. 4) While in the control condition, individual students were seated at their desks and given a set of 5 cubes and a mobile phone to explore the cubes by themselves; in the experimental condition, students sat in pairs and shared the 5 cubes and the mobile phone. Both groups of participants had to answer individually a post-intervention questionnaire with the same questions as in the pre-intervention questionnaire, but posed in different order, so as to assess the learning more accurately. The participants were monitored by three researchers during the interactions. Observation notes were taken regarding struggles with the application, the points students seemed to enjoy most, confusion with any of the tasks, and emotional reactions. The whole experience, including pre-and post questionnaires, took 30 minutes. The experiment material consisted of an android smartphone and the five tangible cubes. Data regarding usability and satisfaction on part of the students were collected using a questionnaire with a Smileyometer [START_REF] Read | Endurability, engagement and expectations: Measuring children's fun[END_REF] Likert scale (it uses pictorial representation) of 5 levels -"1" for totally disagree and "5" for totally agree (see Table 1). The second measurement, related to enjoyment, was gathered through an Again-Again table. This measure is based on the knowledge that people like to do fun things again [START_REF] Read | Endurability, engagement and expectations: Measuring children's fun[END_REF]. We also analyzed which part of the experience was most enjoyable for the participants by answering "Yes" as code 1, "No" code as 0, and "Maybe" as code 2 questions related to each side of the tangible cube (see Table2). To estimate gains in learning outcomes regarding the concepts of the Periodic Table, we used the multiple-choice pre-intervention and postintervention questionnaire data. We also conducted two comparative analyses using a non-parametric test within and between groups

Results

The study aimed to assess whether the use of the AR Serious Game facilitates the learning of concepts related the Periodic Table . We also wanted to analyze whether interventions in pairs had higher gains than individual interventions.

The normality of the sample in terms of results was evaluated, and since the values of Skewness and Kurtosis (p= 0.002) showed that the assumption of normality was violated, we used a non-parametric test. For analysis within each group, we used the Wilcoxon signed rank test, with the game played individually (Control Condition or Group 1) and in pairs (Experimental Condition or Group 2). The results show that the post-intervention learning outcome is significantly higher for participants in the Control condition (Mdn = 2), T= 78, p=0.001, r=0,54 (large effect) as well as in the Experimental Condition (Mdn=1), T=36, p=0.010, r=0.43 (large effect). In sum, the application had a strong, positive effect in the learning of concepts about the Periodic Table in both groups (see Fig. 4).

We conducted a between group analysis -using the Mann-Whitney testwith the same conditions as above. When measuring the children's knowledge before playing the game (Mdn=.00) U= 110.00, p= 0.10, r=-0.31(medium effect), the results show that the difference in learning outcomes between groups was not significant. However, in the post-intervention test, the children that played individually had significantly higher results than those that did the intervention in pairs (Mdn= 1), U= 98.50, p=0.04, r=-2.09 (medium effect). Contrary to the findings of Martín-SanJosé [START_REF] Martín-Sanjosé | Playful interaction for learning collaboratively and individually[END_REF] individual intervention had higher learning gains that in a collaborative setting. We attribute these results to the fact that the participants that did not share the mobile device had more freedom to explore the tangible cube, controlling the areas that they wanted to visualize, the time dedicated to each area, and could repeat the tasks ad libitum (see Fig. 4).

We also performed a Whitney U analysis to evaluate if there were any gender differences in the learning outcomes. From the data, we can conclude that gender differences were not statistically significant (U=139, p=.519). The users were pleased with factors about the usability and engagement of the game (see Table 1). Question 6 (Q6) had the lowest score (Mean=4,25). Few children had difficulties when scanning the cubes images/ markers(see Fig. 4). The Kruskal-Wallis test results do not demonstrate any difference in the usability and engagement of the activity between the groups conditions,χ 2 (1) = 0.22, p = 0.15.

Independent-Samples

Discussion, Limitations and Future Work

Our results reinforce the positive effects of gaming techniques and AR technologies in the engagement and motivation of the students [START_REF] Billinghurst | A survey of augmented reality[END_REF]. According to the questionnaire, the AR visualization of the animated characters/elements introducing themselves to the players was the most enjoyable part of the experience, hence we can infer that the creatures/elements captivating characterizations as funny looking, intriguingly futuristic characters was a successful factor in engaging the children(see Table 2). The participants' reactions show that they enjoy combining the elements through the cube facets that triggered the AR scenes. One of the students commented aloud "I just made water!" and another responded, "I just created a diamond!" According to the data, the 2D animated short stories about the elements were the least captivating part of the experience. Overall, the participants acknowledged that they had learned something new about the Periodic Table . The data also show that the application increased the curiosity of the children regarding other chemical elements.

The results of the preliminary study reported that our game, has positive learning outcomes regarding basic Periodic Table concepts in non-formal settings. Our results also show that there is potential in combining smart phones and Augmented Reality in non-formal spaces to facilitate the learning of content that is not available through the school curriculum, and that this helps to create intrinsic motivation towards future STEM subjects. Young students who came in contact with chemistry through the Periodic Fable game for the first time were able to learn while engaging in the activity.

Exploring all the faces of the tangible cube to gather/visualize information was an intuitive and rewarding process. Nevertheless, some technical challenges were identified regarding the ease of use of the Augmented Reality application. Technical problems such as tracking loss made the interaction difficult for some. Since our application depended on image-based tracking, the experience stopped when moving away from the marker. This was frustrating to some children who wanted to view the animations without being interrupted. Other technical limitations when using AR marker-based technology are dependency on light quality to read the images/markers; delays in the rendering of data; over-heating of the equipment; battery consumption; the need for robust equipment with the required sensors (gyroscope, accelerometer, and compass).

The results of the study enabled us to distill insights that could be beneficial when designing an AR serious game for a young audience: 1) find the appropriate pedagogical framework for the content to be delivered [START_REF] Fisch | Cross-platform learning: On the nature of children's learning from multiple media platforms[END_REF], AR benefits situated and constructive methods; 2) pay attention to the adequacy of aesthetics to the age range; 3) design analogies and metaphors carefully, ensuring that they support the mental images and the construction of ideas needed to facilitate the understanding of the concept; 5) balance the amount of information delivered with the usability load to avoid cognitive overload.

Conclusion

In this paper we have reported on the design and preliminary study of a Periodic Fable AR serious game designed to support children's understanding of abstract concepts such as those found in chemistry. Our study demonstrated that the AR game facilitated the understanding of chemistry and the learning of abstract concepts in non-formal settings. Further research is needed to categorize its benefits and limitations more clearly, and to develop clear guidelines and appropriate tools to address these challenges.

Fig. 1 .

 1 Fig. 1. Left to right -hydrogen, nitrogen, oxygen, chlorine and carbon

Fig. 2 .Fig. 3 . 1 .

 231 Fig. 2. Left: 2D representation of tangible cube; Right -Interaction with the faces. 1. information/animation; 2. Habitat-location of the characters/elements within the Periodic Table; 3. Products that contain the elements; 4. Stories; 5. Combination of the elements; 6. Reactions

  3.2 Participants Demographic and Data CollectionAccording to school curricula in Portugal, Chemistry becomes available as a subject only during the 7th grade, where students are 12 years old. To experiment if the AR based game facilitated the learning of abstract concepts in early childhood we decided to evaluate our game with children before they had engaged with abstract concept of chemistry as a school curricular activity. We based our study at a Computer Science Club at a public school in Madeira. We engaged 36 participants, 20 females (55.6%) and 16 males (44.4%) ranging from 8 to 11 years old. The study was designed as in between study, where 18 participants experienced the Periodic Fable in pairs (50%)-Experimental Condition or Group 2, while 18 individually (50%) -Control Condition -or Group 1. The study was designed to explore if the AR game would support the learning of abstract concepts such as chemistry basic, in children with no previous exposure to the subject and to explore which interaction conditions (single or pairs ) would yield the best learning outcome. The study took place during one day, on November 27, 2019.

Table 1 .

 1 Usability and engagement data results

	Q# Question	Percentage Mean / SD
	Q1 I enjoy using Periodic Fable	88.9%	4,89/0.319
	Q2 It was easy to use the application	55.6%	4,39/0.803
	Q3 I knew what to do during the game	75%	4,72/ 0.513
	Q4 The instructions were easy to follow	61.1%	4,53/0.696
	Q5 I always knew what to do during the game	52.8%	4,11/1.214
	Q6 The capture of the information with the markers always worked 44.4 %	4,25/ 0.770
	Q7 The camera never lost the information of the marker	55.6%	4,29/0.926
	Q8 The application always read the correct marker	77.8 %	4,67/0.717
	Q9 It was a great experience to play the game	88.9%	4,83/0.561
	Q10 I was always performing the same action during the game	58.3%	4,36/0.961
	Q11 The amount of information was enough	69.4%	4,58/0.692
	Q12 The 3D objects always appeared on my mobile screen	66.7%	4,56/0.695
	Q13 There was a tutorial	75%	4,67/ 0.676

Table 2 .

 2 Again and Again / Engagement scale

	Q# Question

Acknowledgments

This work has been supported by LARSyS-FCT Plurianual funding 2020-2023 (UIDB/50009/2020), MITIExcell(M1420-01-0145-FEDER-000002), MADEIRA 14-20 FEDER funded project Beanstalk (2015-2020) and FCT Ph.D. Grant PD/BD/150286/2019. Our gratitude also goes to the students and computer science teacher at Escola Básica de Santa Cruz. We would like also to thank Gonçalo Martins, Michaela Sousa, Rui Trindade and Manuel Fontes for their ongoing support.


Yuexian Gao
email: gaoyuexian@jaist.ac.jp

Mohd Nor

Akmal Khalid

Hiroyuki Iida
email: iida@jaist.ac.jp

Finding flow in training activities by exploring single-agent arcade game information dynamics

Keywords: Arcade games, Game refinement theory, Risk frequency ratio, Flow

This paper incorporates discussion about game refinement theory and the flow model to analyze simulation data collected from two types of arcade games. A mathematical model of the arcade game processes is formulated. The essence of the arcade games is verified through the game-playing processes of players. In particular, challenge setup could contribute to the addictiveness when the mode is close to flow channel. Risk frequency ratio is applied to measure the process and verified the more entertaining mode of training activities.

Introduction

Arcade games firstly referred to entertainment machines installed in public businesses such as restaurants, bars, and amusement centers. Since Apple company launched the arcade games project in 2019 4 , arcade games have entered the limelight with a new look. The term "arcade game" nowadays refers to action video games that designed to play similarly as an traditional arcade game in the game center, with frantic and addictive game-play. It focuses on the user's reflexes, while usually feature very little puzzle-solving, complex thinking, or strategy skills 5 . Csikszentmihalyi introduces a mechanism to get into the flow which refers to a state of deep enjoyment as an approach to a better life. Playing games is a process of eliminating the uncertainty of game outcome, which is regarded as a typical flow activity [START_REF] Csikszentmihalyi | Beyond boredom and anxiety[END_REF].

The measure of game refinement (GR) had been used for evaluating sophistication of various games [START_REF] Iida | Serious games discover game refinement measure[END_REF]. This study aiming to analyzed game process model identifying players' addiction to the arcade games and similar functional activities. By applying the GR measure, this study is interested in finding the core constitution of an enduring training process.

Related Works

A great game "takes one minute to learn but a lifetime to master" [START_REF] Kunkel | How alex pajitnov was tetris-ized! why tetris' creator got the cultural bends upon his arrival in america[END_REF]. Arcade games perfectly illustrate this feature. "Pong" is the first to appear successfully in the commercial market of the public in 1972 and lead the arcade game gradually into industrialization. Over the decades, although arcade games have been greatly improved in both form and content, their core feature is still as "simple but fun to play". Some researchers focus on specific arcade games as objects to re-design the games, test advanced algorithms, or find solutions for human activities. Schrittwieser et al. proposed MuZero by introducing an approach combining both high-performance planning and model-free reinforcement learning methods [START_REF] Schrittwieser | Mastering atari, go, chess and shogi by planning with a learned model[END_REF]. The MuZero does not require any knowledge of game rules or environment dynamics, tested on 57 Atari arcade games and achieved "a new state of the art". Cook et al. demonstrated the approach to generate complete arcade games by ANGELINA system, scratched by combining rulesets, maps, and object layouts that has designed itself [START_REF] Cook | Multi-faceted evolution of simple arcade games[END_REF]. More recently, studies began to explore the practicalities of using games for learning. Rohlfshagen et al. summarized the peer-reviewed research from sociology, psychology, brain-computer interfaces, biology and animals, education, which focused on either game with particular emphasis on the field of computational intelligence [START_REF] Rohlfshagen | Pac-man conquers academia: Two decades of research using a classic arcade game[END_REF]. They believed the potential usefulness of arcade games like Pac-Man for higher education is promising.

In essence, arcade game studies mainly focuses on aspects such as (1) using arcade games to assist psychological experiments, (2) improving the efficiency of algorithms, and (3) using arcade games for learning. Nevertheless, research discussing the essence of arcade games from the dynamic of the game perspective is limited to discover optimal flow experience in game-playing processes.

3 Assessment methodology

Game refinement theory

Game refinement (GR) theory [START_REF] Iida | An application of game-refinement theory to mah jong[END_REF] is used to measure the sophistication (i.e., the balance between luck and skill) of a game. It provides an innovative game dynamics view by evaluating the process of a game, simulating the game outcome's uncertainty as a kind of force in mind, which is corresponding to force in nature based on Newton's second law [START_REF] Sutiono | A Mathematical Model of Game Refinement[END_REF].

From the perspective of players, information of the game outcome is a function of time t (in board games would be the number of possible moves). By considering the process of game as a process of solving uncertainty of game outcome (or obtained certainty) x (t), (1) is obtained.

x (t) = n t x(t) (1)
The parameter n (1 ≤ n ∈ N ) is the number of possible options and x(0) = 0 and x(T ) = 1. Here x(T ) stands for normalized amount of solved uncertainty. Note that 0 ≤ t ≤ T, 0 ≤ x(t) ≤ 1. The above equation implies that the rate of increase in the solved information x (t) is proportional to x(t) and inverse proportional to x(t) and inverse proportional to t. Then, ( 2) is obtained by solving [START_REF] Cook | Multi-faceted evolution of simple arcade games[END_REF].

x(t) = ( t T ) n (2)
In most of the board and continuous movement video games, total length of the game is significantly different for players with different levels. For example, Tetris, there will be no end for the perfect player theoretically. We assume that the solved information x(t) is twice derivable at t ∈ [0, T ]. The second derivative here indicates the accelerated velocity of the solved uncertainty along with the game progress. After the second derivative, the measure of GR can be formulated in its root square form, where GR = √ n(n-1) T

, as shown by [START_REF] Csikszentmihalyi | Toward a psychology of optimal experience[END_REF].

GR 2 classical = n(n -1) T n t n-2 | t=T = n(n -1) T 2 (3)
It has been found that sophisticated games have a similar value of game refinement located at the zone GR ∈ [0.07, 0.08] [START_REF] Sutiono | A mathematical model of game refinement and its applications to sports games[END_REF][START_REF] Gao | Nature of attractive multiplayer games: Case study on china's most popular card game-doudizhu[END_REF][START_REF] Xiong | Possible interpretations for game refinement measure[END_REF]. Another term n(n-1) correspond to the game progress patterns such as one-side game and seesaw game, or the difficulty of completing the task.

Game refinement measure for target games

Acceleration in mind for arcade games For arcade games those aim playing as long as players can, the measure of game refinement should be reviewed from a more general and macroscopic perspective, the speed of uncertainty being solved is uniformly accelerated. Thus, total uncertainty of game outcome x(t) = vt. Consequently, the speed of a game playing, denoted as v, could be counted as the successful ratio to choose the best choice approaching to the end of the game process, namely v = 1 T . Therefore, risk frequency ratio is defined as

m = 1 -v = T -1 T
. Note that m is dynamic since the player would often feel risky when their skill is weak during the process, and as the players get more skills by practicing, m would decrease.

Gamified experience in single-agent arcade games could be taken as the addiction level of the game. Hence, m could be regarded as the predictor variable of the game challenge. We assume m is the difficulty to move the game forward. Supposing the game ends at t = T , solve that x(T ) = vT = 1 2 aT 2 , we could get acceleration in mind, namely a-value for single arcade games in this study, as

.

a = 2v T (4)
Flappy Bird Flappy bird was released in 2013 developed by Vietnamese video game artist Dong Nguyen. It had been the most downloaded mobile in the app store for IOS, with a download amount of 50 million per month, during which the developer earned 50,000 dollars a day from the in-app advertisements. Process of Flappy birds is uniformly related to learning something or training to acquire some skill. In our simulated Flappy bird game, the player gains a score every time crossing through a pipe is successful. The total game length T is the total number of counted tries, i.e., the number of pipes, thus the successful tries always be one less than the total number. Hence the success ratio v here would be Passed Pipes Total Tries . Hence, the a-value of Flappy bird is calculated as [START_REF] Iida | Serious games discover game refinement measure[END_REF].

a FlappyBird = 2*Successful Ratio Total Tries (5)
Brick Car Racing The game Brick Car Racing is a dedicated handheld game console popular in the early 1990s 6 . A simplistic racing game in which the player switches between left and right lanes to avoid other cars passing through. The player loses if the car hits one of them. The higher the level, the game's speed will be faster.

In our simulation of the game, the player gains score whenever the car successfully avoids a collision. Therefore, the total game length of this game is the total times that the player needs to slide, which is the number of an encounter of the opposing cars. Unlike the Flappy bird, for every specific number of passes, the game would level up, and the difficulty would increase by increasing the car speed. As the speed suddenly changes, a sudden sense of weightlessness is expected by the players. Hence, the wining speed (v) should be decreasing. From the perspective of risk frequency ratio (m), the player experience towards sudden level changes (speed) is considered. For the Brick Car Racing, risky frequency ratio is measured from level to level. For instance, if there are 100 people participate the level 1, 70% of them passed where the m at level 1 is 30%. Among the 70 people, 35 (50%) of them passed level 2. Then, m at level 2 is 50%, and not 65% since the calculation is not included in the previous stages (30% percent of the players excluded from the latter risk). Hence, referring to the formulation in Section 3.1, the a-value measure of the Brick Car Racing is given as [START_REF] Iida | An application of game-refinement theory to mah jong[END_REF].

a BrickCarRacing = 2 * Level based Success Speed Passed Car At The Level (6)

Flow Theory and force in mind

Flow, originally derived from Csikszentmihalyi's observations of artists, chess players, climbers, and composers. He observed that when these people were engaged in their work with almost total concentration, often losing track of time and awareness of their surroundings [START_REF] Csikszentmihalyi | Toward a psychology of optimal experience[END_REF]. They engaged in their individual activities out of a common sense of fun. These pleasures are derived from the process of activity, and the external rewards are minimal or non-existent. This flow experience caused by concentration is considered to be the best experience usually happening when skill people acquired and challenge they faced at a comparable level. The formula is shown as F low = Skill Challenge (the goal is 1.0). From the view of game informatics, with the decreasing of m, people would feel boring since the game is with no longer has much uncertainty for the player as at the beginning. They would come to the phase corresponding to the boredom zone in flow theory when an event needs high skill but with low challenge.

In nature physics, force is any interaction that will change the motion of an object when unopposed. Force can cause an object with mass to change its velocity (which includes to begin moving from a state of rest), i.e., to accelerate Therefore,

F = ma = 2mv T (7)
As discussed in Section 3.1, the acceleration in mind could be the measure about ratio of skill and challenge. In order to maintain the movement of game or activity, force should not be decreased, therefore, force in mind could be the measure of flow state. The bigger the force in mind is, the higher possibility the game could be in the flow longer.

Data and analysis and discussion

The essence of game attraction is uncertainty [START_REF] Iida | Serious games discover game refinement measure[END_REF]. From the information perspective we could also agree that n = 2 is the most competitive case when the win rate and lose rate are equals, i.e. where the game outcome entropy7 reaches the highest value. In this study, two arcade games were considered for data collection. The open-source code is adopted and simulation is conducted by using PyGame. The Flappy bird, whose challenge setup is constant, as well as the Brick Car Racing with increasing difficulty. Although the interface and presenting form of the two games are different, the core playing model is similar, which is moving the character to avoid collision on obstacles to play as long as possible. The two classic games could represent for many popular arcade games recently such as Temple Run(as well as other Run games), Shooty Skies, Jump Jump. The Flappy bird and Brick Car Racing games represent two typical basic singleagent arcade games. One represents for those with constant difficulty while the other for those with changing difficulty. After all the data has been aggregated, the game refinement value of target games is shown in Table 1. Data shows that the measure of game refinement are similar for the two games, both of which are lower than the most refined GR zone. Previous work on serious games reveals that activities that happened in a serious environment would not be as entertaining or relaxing as fun games. In such a situation, game elements are used to increase motivation and engagement of the learning process so that the GR value will be much lower [START_REF] Iida | Serious games discover game refinement measure[END_REF]. Flappy Bird has a-value of 0.059, and Brick Car Racing is 0.055, both locate between fun game and serious game. However, the force in mind is differs significantly. The bigger force of Brick Car Racing implies the game is has more flow force, which can maintain a longer period of flow state. With difficulty increased, the expected risk of the player is (kind of) reset. When the players gradually relax their vigilance and become more comfortable, the game suddenly accelerates, and then the players become excited again. This situation is validated by the depiction of the game process of the Brick Car Rac-ing that changes dynamically (m value in Figure 1). As the process repeats, the player experiences weightlessness similar to that of a roller coaster, keeping them always curious about the outcome; thus, the player would get highly attracted.

The activities with skill changing perform as the trend as a blue line in Figure 1 are training activities, which mostly driven by an sense of accomplishment. More often than not, it is a steady, repetitive process. While activities with trend given as red in Figure 1, skill increase defines the training activities as entertaining. As the game difficulty increasing, player skill gets better; and as player skill improves, the challenge gets harder, and so on. This kind of activity stems from people's instinctive curiosity about the unknown and is an implicit kind of entertainment. Thus, the relationships between boring training and gamified training are established. The difficulty that suits the player's skill level needs to be dynamically changed to keep the player engagement stays within the flow zone. The process of keep playing single-agent arcade games is boring training. The more attempts the player has, the more skillful they will be. As they become skillful, they are less likely to play the game or do the training. If the game difficulty is adjusted, the training process can become more exciting and long-lasting. The result showed in the Figure 1 could be aligned with the flow model in theory and in practice as shown in the Figure 2.

The game process of the arcade game is metaphorically a continuous training process. The fluctuation of GR in Figure 1 indicates an information process similar to ride a roller coaster, which can keep the player stay in the "challenge equivalent to skill" state, as shown in Figure 1. Therefore, the regulation of single-agent arcade games would be the benchmark for us to understand the training process and to overcome the persistence at the later phase of skill training.

Conclusion

This study uses two typical single-agent arcade games as a benchmark to study the arcade game's essence where game refinement measure were applied and data were collected and analyzed. Flow experience in theory and real cases were described where a logical model of the arcade game process was formulated. Result shows when the risk frequency ratio changes irregularly and repetitively, the process is more likely to be in the flow state in reality. The difficulty increases with the level case is closer to flow and was verified by the measure of game refinement. It offers us inspiration if we need to turn a training event engaging and long-lasting; the game difficulty needs to be adjusted dynamically based on the player's increase in skill. This finding will contribute to serious game design to help people learning things persistently.

2 Fig. m value

 2 Fig. m value change with level increase in Flappy Bird and Brick Car

Fig. 2 .

 2 Fig. 2. Flow in theory and in practice

Table 1 .

 1 The measure of game refinement of target arcade games

	Game	v	m	n	T a	F
	Flappy Bird 0.9414 0.0586 1.0689 32 0.059 0.00345
	Brick Car Racing 0.5506 0.4494 1.8161 20 0.055 0.02474

https://www.apple.com/newsroom/2019/09/apple-arcade-invites-you-toplay-something-extraordinary/

[START_REF] Iida | Serious games discover game refinement measure[END_REF] Arcade Game, http://en.wikipedia.org/wiki/Arcade_game

https://retroconsoles.fandom.com/wiki/Brick_Game

H(X) =i P (xi) log b P (xi), information entropy by C.E., Shannon.


Robert Fronek

Barbara Göbl

Helmut Hlavacs
email: helmut.hlavacs@univie.ac.at

Procedural Creation of Behavior Trees for NPCs

Keywords: Behavior trees, Machine learning, Procedural creation

Based on an emerging need for automated AI generation, we present a machine learning approach to generate behavior trees controlling NPCs in a "Capture the Flag" game. After discussing the game's mechanics and rule set, we present the implemented logic and how trees are generated. Subsequently, teams of agents controlled by generated trees are matched up against each other, allowing underlying trees to be refined by learning from victorious opponents. Following three program executions, featuring 1600, 8000 and 16000 matches, highest scoring trees are presented and discussed in this paper.

Introduction

Despite its major impact on gaming experience, creating artifical intelligence (AI) for games is increasingly pushed towards late stages of the development process, freeing resources for easily marketable features such as graphics [START_REF] Nareyek | AI in computer games[END_REF]. Thus, one can currently observe a trend towards automatically generated AI in the industry [START_REF] Owen | AI for game production[END_REF]. These approaches allow for procedural generation of opponents that are still able to display different behaviors.

The following paper presents a program that procedurally generates behaviour trees (BT) for a simple "Capture the Flag" game. Games have a fixed set of rules and possible interactions, making them ideal candidates to test the capabilities of an AI [START_REF] Schaeffer | A gamut of games[END_REF]. The quality of an AI is evaluated by matches between randomly generated BTs. When a BT is defeated, it is discarded and replaced by a new one, which, after a sufficient number of matches, eventually leads to a BT that is superior to a large number of other, randomly generated BTs. The game, despite its turn-based approach, shares various aspects with real-time strategy (RTS) games, such as commanding units, strategic decision making and aiming for both short-and longterm goals [START_REF] Robertson | A review of real-time strategy game AI[END_REF].

Related Works

Several previous works discuss applications of automated BTs. Lim et al. [START_REF] Lim | Evolving behaviour trees for the commercial game DEFCON[END_REF] managed to defeat the AI of the game "DEFCON" through evolution and combination of BTs. Abiyev used BTs to control soccer robots [START_REF] Rahib H Abiyev | Control of soccer robots using behaviour trees[END_REF]. Dromey points out that BTs are a good alternative to automated AI, due to a clear connection of requirements and formal specifications [START_REF] Dromey | Using behavior trees to model the autonomous shuttle system[END_REF]. This allows to generate requirementbased BTs.

Game Mechanics

The game is played on a board comprising a total of 56 (7x8) fields. Each field can only be occupied by one agent. If another agent, either ally or enemy, is already placed on a field an agent cannot move onto it. There are three types of terrain for each field:

-Open: Every agent can move onto this field, there are is no bonus or penalty.

-Blocked: No agent can move onto this field. Agents may shoot across the field with no bonus or penalty. -Cover: Every agent can move onto this field. Additionally, damage is reduced when placed on this field if attacked from the front. Damage from melee attacks is not reduced, neither is damage from attacks originating from behind or either side.

Figure 1 shows the game's board. Two fields, symmetrically placed, are blocked (marked "x"). Additionally, there are 4 fields of type "cover" (marked: "c") in the field's center as well as next to the blocked fields. The flag's position is marked "F". Numbers indicate x-and y-coordinates as used by the game's internal logic. Sweetser et al. [START_REF] Sweetser | Current AI in games: A review[END_REF], define (software) agents as goal-driven entities that are aware of their environment. In this work, agents operate based on a number of parameters as described below. The AI's success determines whether chosen actions are suitable to support the game's goal.

Agents initially possess 25 health points (HP) and can perform ranged and melee attacks. If the HP value decreases to 0 or less it is defeated and removed from the game. Ranged attacks can be carried out 2 times before ammunition needs to be reloaded. Reload is either initiated by explicitly performing the corresponding action or happens automatically if a ranged attack is conducted without ammunition, thus replacing the attack action. There are 9 possible actions for an agent. Each turn, an active agent (i.e. an agent that has not been defeated yet) performs one of the following actions:

-Move towards an enemy: The agent looks for nearby enemy agents on the field. If none are left, he moves towards the opposing team's flag instead. Distances are measured in fields and the agent may move one field horizontally or vertically per turn. Vertical movements are prioritized over horizontal movements until the opposing agent is positioned at the same row. If a field is blocked, the agent moves sidways at a 90 • angle to the initially calculated direction. If none of these movements is possible, the agent can perform no more action in this turn and stays in place. -Move towards the enemy's flag: The agent moves one field towards the opposing team's flag. Similar to the previous action, vertical movement is prioritized if possible and necessary. -Move towards the own team's flag: The agent moves one field towards their own team's flag. Again, vertical movements precede horizontal movements.

-Heal: The agent stays in place and restores a small amount of HP.

-Shoot enemy agent: The agent shoots the nearest enemy agent. Damage is higher, the closer the other agent is. Shot agents take increased damage if attacked from their sides (double damage) or behind (triple damage). In both cases, "Cover" fields do not reduce damage. If an agent is in cover, frontal damage is reduced by half. If no ammunition is left, the agent reloads instead. -Perform melee attack: The agent attacks an enemy agent on an adjacent field, doing damage dependant on the attack's direction. Sideway attacks do double damage while attacks from behind immediately defeat the attacked agent. If there is no enemy on adjacent fields, the agent moves towards an enemy instead. -Flank: The agent preferably tries to move on a field directly behind an opposing agent, or, alternatively, to the side of an opposing agent. -Reload: Ammunition is restored to 2.

-Idle: The agent stays idle.

Logic

Each team generates a BT to decide which actions an agent performs. The BT is a binary tree where all internal nodes are logic nodes and leaf nodes repres-ent actions. Each logic node represents a comparison with a randomly chosen operator and a threshold. One of the following comparisons may be assigned:

-Distance from the own flag to its closest enemy agent -Distance from the closest enemy agent to self -HP of self -Distance from self to the enemy's flag -Remaining ammunition -Whether self is in cover -Whether closest enemy agent is in cover -Number of nearby allied agents (teammates) -Number of nearby enemy agents Possible operators are ≤ (less or equal) and ≥ (greater or equal). Thresholds are randomly assigned from predefined ranges. Distances are assigned between a range from 1-15 as 15 is the maximum distance on a 7 x 8 board (based on the 1 norm). Agents' HP range from 0-25, ammunition ranges from 0-2. Checking whether the agent itself or enemy agent's are positioned on "Cover" needs no threshold as it is a logical query. Nevertheless, 0.5 is assigend to avoid NULL values. To query for nearby enemy agents, two parameters are needed. A threshold, assigned between 1 and 4, limits the amount of agents that are looked for. The second parameter defines the maximum distance of fields for the search, possible values range from 1-6.

Trees are generated as follows: 4-12 actions are randomly assigned to leaf nodes, with corresponding 3-11 internal logic nodes holding randomly assigned comparisons and operators. Subsequently, a threshold and, if needed, a second parameter are assigned randomly. Tree traversal starts by evaluating the logical statement in the root node. If true, the left child is visited, otherwise the right child is visited. If the next node is a logic node, traversal continues as described, if it is a leaf node, the corresponding action is performed. Active agents decide which action to perform by traversing the tree each turn.

Methodology

Ponsen et al. [START_REF] Ponsen | Automatically generating game tactics through evolutionary learning[END_REF] show, that dynamic AIs which adapt based on victorious strategies are superior to static AIs. Thus, defeated AIs should learn from victorious BTs and try to adapt to their strategies.

At first, BTs are generated for 32 teams. Teams are then paired against each other and initialized with a score of 1. Subsequently, each team keeps count of their victories. Victorious teams increment their score by 1 plus half of the points (rounded down) of the defeated team, except for victors in the first round who double their score to 2.

Generation of a New Tree (No Draw)

The defeated team's tree is generated based on both opposing parties' trees. Size of the tree is randomly assigned from 3 options: size of the victorious team's tree, size of the defeated team's tree or a randomly assigned new size. Similarly, each node is randomly inherited from the corresponding node from either tree or randomly generated. If the algorithm tries to base a node on a pre-existing tree with smaller size holding no corresponding node, it falls back to the other tree's nodes, or, ultimately, random generation of a new node.

Generation of new trees is based on weighted decisions. First, the upper limit l of a range is determined by the victorious team's score (S v ), the defeated team's score (S d ) and a constant of 5, to allow for randomly assigned nodes, as follows: l = S v × 3 + S d + 5. A random number x is generated within the range of 0-l. If x < S v ×3, nodes are inherited from the victor's tree, if S v ×3 ≤ x < (S v ×3+S d ) nodes are inherited from the defeated tree. If the random value is greater or equal to the latter limit (x ≥ (S v × 3 + S d )), a randomly generated new node is assigned. This enables defeated teams to "learn" from victors but still allows for improvements based on random adaptations.

Example: A team with a score of 7 (S v = 7) defeats a team with a score of 2 (S d = 2). This results in a range of 0-27 for the randomly generated number x. If 0 ≤ x < 21, the node is inherited from the victorious team's tree. If 21 ≤ x < 23, the node is inherited from the defeated team's tree. Finally, if x ≥ 23 a new node is generated randomly. These newly generated trees are assigned a score S, where S = 1 + (S v + S d )/10 .

Generation of a New Tree (Draw)

If no team is victorious after 100 turns, the game results in a draw. Typically, if a team wins eventually, a game lasts about 15-40 turns. Thus, probability of a draw is higher if a game goes on beyond 40 turns. Considering the random generation of trees, draws might e.g. be caused by trees that never move an agent towards the enemy flag. In this case, both trees are replaced, where one tree is generated based on both team's trees as described above (one tree is assumed as victor). The other tree will be generated from scratch and initialized with a score of 1.

In-between matches

After each match, the victorious team's score is checked against the current high score. If the team has a higher score, the new high score is saved and it's underlying tree is saved for output after completion of all matches. Additionally, the previously highest scoring tree is now ranked second and will also be outputted. Eventually, the vector holding all teams will be shuffled to create new pairings. After a predefined number of matches, the program terminates and outputs the two highest scoring trees and general statistics (see Table 1).

Results

The program was executed 15 times, 5 times each for 100 rounds (1600 matches), 500 rounds (8000 matches) and 1000 rounds (16000 matches). The most super-iour trees of each set are discussed below.

Analysis of Trees

Table 1 provides some first insights. Despite a higher number of matches, results show a roughly equal rate of draws. In a match between two "competent" AIs, a draw is rather unlikey, due to the first-move advantage. This suggests, that a rather constant rate of "inapt" AIs (AIs that do not move towards the opponent's flag) is generated during program execution.

Program execution characterized by higher scores result in less matches ending in a draw. It can be safely assumed, that this is due to early generation of a superiour AI that subsequently defeats its opponents and serves as a basis for opponent's to learn from. The first run featuring 500 rounds illustrates this issue very well, as a low high score is accompanied by a high number of draws, which suggests that random generation of BTs did not produce a superiour AI for some time.

The gathered data during program execution also shows that a higher amount of rounds does not result in higher scores. One could naively assume that 5 times as many rounds result in at least 5 times higher scores -or even more, as a superious AI might gather more points from defeated, but previously succesful, opponents. A possible explanation might be that defeated AIs learn rather quickly from superior AIs which eventually leads to equally "competent" opponents.

Analysis of superior trees (100 Rounds)

Tree 1 (Figure 2) features a "Enemy in Cover" query in its root node (true represented by 1, false by 0). However, the query is more likely to return false, which results in more frequent traversal of the left side of the tree. Please keep in mind, that the tree is traversed according to the following rules: if a query returns true, the left child is visited, otherwise the right child. "Enemy Distance to Flag" is always less than 13 as long as there are active, opposing agents, leading to traversal of the right children of this node. This results in a mostly defensive behaviour: agents wait, in close distance to their own flag, for opposing agents to advance and shoot them when in reach. As soon as all opposing agents are defeated, querying "Enemy Distance to Flag" returns a value of 1000, leading the agents to try to flank. As there are no further opponents and the flag can not be flanked, agents move directly towards the other team's flag instead. Similar behaviour can be observed when opponents are in cover: agents move towards their own flag or reload ammunation. As there are is no cover in immediate distance to the flag, the AI may easily defend its flag.

Tree 2 (Figure 3) mostly leads to melee attacks: the root node likely returns false as all allied agents still have to be active and nearby. Agents move towards the enemy if no enemy is nearby and subsequently move towards the flag if no opposing agent is still active -resulting in a simple, but efficient tree. The right side of Tree 3 (Figure 4) is rarely traversed, as an agent's HP are likely higher than 3.76. The AI lacks opportunity to use ammunition and will therefore mostly perform melee attacks unless many enemies (> 3.28) are nearby and the agent heals itself. Similiar to some previous trees, tree 6 (Figure 6) will mostly perform melee attacks. If many allied agnets are nearby, they might stay in cover. Nevertheless, as fields providing cover are limited, some agents will continue to attack.

In contrast, tree 7 (Figure 7) displays a new approach: the team will split up and try to reach the enemy's flag as fast as possible.

Tree 8 (Figure 8)will likely resort to melee attacks as well. However, if HP are low, ranged attacks are more likely. Tree 9 (Figure 9) displays a more balanced behavior. Agents peform both melee and ranged attacks, except in case of many nearby enemies, which lead to a retreat towards the own flag. This trees displays strategic, team-based behavior and scores highest during execution with 500 rounds and its high score is only topped by one tree in the 1000 round scenario. Tree 11 (Figure 10) and tree 12 (Figure 11) display well known patterns resulting in melee attacks. Amount of ammunition never lowers, as agents never shoot and the distance to the flag will always be less than 14. Tree 13 (Figure 12) also mostly results in melee attacks. If many enemies are nearby, agents will constantly reload ammuniation until other allied agents have dealt with aforementioned enemies.

On first inspection, tree 14 (Figure 13) might favor "move" and "reload" actions. However, due to the randomized definition of "near", the leaf node Tree 15 (Figure 14) displays a more differentiated behavior. As long as enemies are not nearby, agents will move towards them based on the "Melee Enemy" instruction. Otherwise, agents attack enemies depending on whether they are in cover. If enemies are not in cover, agents shoot them. In case enemies are in cover agents resort to melee attacks, which do more damage to enemies in cover.

Conclusion

There is a clear trends towards "simple" trees, which are somewhat obfuscated by hardly traversed branches. Further work might take a closer look on these rarely visited branches and nodes and deliver further insights. Furthermore, trees could be refined by reordering nodes, as suggested by Utgoff et al. [START_REF] Paul E Utgoff | Decision tree induction based on efficient tree restructuring[END_REF]. This helps to address the issue of branches that could not be reached previously.

If actions can not be performed, resorting to more suitable, alternative actions leads to lesser draws. However, this also favors rather simple trees performing the same action repeatedly. Randomly generated trees also often feature branches that cannot be reached, leading to frequent traversal of branches featuring effortless and simple actions in their leaf nodes. These trees are also more likely to

Figure 1 .

 1 Figure 1. Empty Board

Figure 2 .

 2 Figure 2. Tree 1 -100 rounds, run 1, score: 54

Figure 3 .

 3 Figure 3. Tree 2 -100 rounds, run 2, score: 43

Figure 4 .

 4 Figure 4. Tree 3 -100 rounds, run 3, score: 41

Figure 5 .

 5 Figure 5. Tree 4 -100 rounds, run 4, score: 47

Figure 6 .Figure 7 .

 67 Figure 6. Tree 6 -500 rounds, run 1, score: 34

Figure 8 .Figure 9 .

 89 Figure 8. Tree 8 -500 rounds, run 3, score: 61

Figure 10 .Figure 11 .

 1011 Figure 10. Tree 11 -1000 rounds, run 1, score: 50

Figure 12 .

 12 Figure 12. Tree 13 -1000 rounds, run 3, score: 60

Figure 13 .

 13 Figure 13. Baum 14 -1000 rounds, run 4, score: 56

Table 1 .

 1 Table 1 provides further data on program execution and results, such as number of victories, draws and high scores (HS). General statistics

	Rounds		100		500	1000
	Run Victories Draws HS Victories Draws HS Victories Draws HS
	1	1451	149 54 5913	2087 34 13238 2762 50
	2	1425	175 43 6887	1113 49 14027 1973 75
	3	1427	173 41 7577	423 61 13308 2692 60
	4	1362	238 47 6683	1317 69 13004 2996 56
	5	1458	142 50 6776	1224 48 14026 1794 53
	Avg	1224.6 175.4 47 6767.2 1232.8 52.2 13520.6 2479.4 58.8
	%	89,0% 11,0%	84,6% 15,4%	84,5% 15,5%

Procedural Creation of Behavior Trees for NPCs


Alexander Ramharter

Helmut Hlavacs
email: helmut.hlavacs@univie.ac.at

Survival On Mars -A VR Experience

Keywords: Virtual Reality, Survival on Mars, Wrong Assumptions

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In recent years, the colonization of Mars has reached popular culture to an extent where even SpaceX CEO Elon Musk has frequently addressed this topic through interviews and his social media channels [START_REF]Missions To Mars[END_REF][START_REF] Mcfall-Johnsen | Elon Musk says he plans to send 1 million people to Mars by 2050 by launching 3 Starship rockets every day and creating ' a lot of jobs' on the red planet[END_REF]. But building a liveable and enjoyable habitat on the red planet is very difficult. Conditions on Mars are hostile, and humans can only live there with massive restrictions. The aim of the work is to build a virtual reality experience which demonstrates a typical day on Mars in an entertaining but also informative way. The goal is then to confront the player with some of the problems a potential marsian inhabitant would have, and evaluate the results of the players reactions. Especailly, we answer the following questions:

1. What are the major problems of living on Mars? 2. How can you implement those problems in an interactive Virtual Reality experience? 3. How do people perceive living on Mars before and after the experience?

Related Work

Virtual reality is now in its heyday, as big publishers slowly begin to deliver significant titles. At least since the introduction of virtual reality for the smartphone it has reached big popularity and became more affordable for the end consumer. Due to the high immersion VR provides, many game developers try to create "worlds" which users cannot explore in real life. Since the surface of Mars is still untouched by humans it makes up for a perfect and exciting setting for developers as well as for the players.

One of the more detailed implementations of a VR-Experience on Mars is "Mars 2030" [START_REF]Mars 2030 VR Experience[END_REF]. It was created by Fusion Media Group in cooperation with NASA and let's you explore an accurately-mapped terrain from satellite footage. Not only can you discover the surface of Mars by foot but also with a rover. The Virtual Astronaut [START_REF] Wang | Virtual Astronaut for Scientific Visualization-A Prototype for Santa Maria Crater on Mars[END_REF] is a tool which can create a virtual 3D environment. It is interactive and is built on the Unity engine [START_REF]Unity. Unity[END_REF]. A first prototype was created for the Santa Maria Crater on Mars. Scientists can use this tool for example to measure distances on the surface in an very intuitive way. Mental health of the crew members during long term space missions is very important. In [START_REF] Salamon | Application of Virtual Reality for Crew Mental Health in Extended-Duration Space Missions[END_REF], the authors examined the use of virtual reality to help sustain mental health during simulated typical situations which are usual on NASA missions. Their results show that due to the capabilities VR provides, a good preparation for the Astronauts can be achieved, but there is still more research in this field necessary. Besides the work mentioned above, it is worth mentioning that there are many 360 videos on the internet which also provide impressive immersion. Since nearly every phone nowadays support 360 video playback function, many people can benefit of this feature.

Conditions on Mars

Due to elaborated costs, it would not be possible to transport all resources to Mars from Earth. This means astronauts have to rely on in situ resource utilization (ISRU). This leads to many complications, as the Mars has much different environmental parameters than earth. To keep the virtual reality experience focused on the essential things and the message simple, it concentrates on 6 major conditions -respectively problems as detailed below.

Breathing on Mars: The surface pressure on Mars lies between 5 to 11 hPa which is about 1% compared to earths atmospheric pressure [START_REF] Verseux | Sustainable life support on Mars -the potential roles of cyanobacteria[END_REF]. That means the human body has to be protected by a pressure suit, otherwise the liquids would boil away within minutes. Oxygen has to be extracted from the athmospheric carbon dioxide or from the chemical hazard Perchlorate found in Marsian soil.

Producing Water: Against common belief there is plenty of water on Mars, though it mostly exists as ice. Some of it exists as vapor in the atmosphere [START_REF] Jakosky | The seasonal behavior of water on Mars[END_REF]. Because of the low atmospheric pressure, water on Mars only comes in those two forms. That is why melting the ice would lead to vaporizing the water instantly.

Toxic Soil: Due to the high concentration of Perchlorate the martian soil is toxic [START_REF] Wadsworth | Perchlorates on Mars enhance the bacteriocidal effects of UV light[END_REF]. This makes the process of growing crops extremely difficult. A lot of research takes place in this field [START_REF] Wamelink | opag[END_REF].

Radiation: In contrast to earth, Mars unfortunately does not provide a magnetic field or a dense atmosphere that could protect the planet from space radi-ation. The International Space Station (ISS) also is not protected by an atmosphere but still is in the range of the earths magnetosphere. This is why radiation exposure on Mars is two to three times higher than on the International Space Station.

Extreme Temperatures: With a median temperature of -60 • the surface of the red planet is much colder than the earth's [START_REF] Verseux | Sustainable life support on Mars -the potential roles of cyanobacteria[END_REF]. This does not only mean that home bases and green houses will have to have a very good isolation and heating, but also that machines and robots have to cope with that -just like Curiosity uses plutonium not only to power itself [START_REF]Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) -Factsheet[END_REF].

Generating Power: One way of producing enough energy for survival is to use solar power, like it was used for example on the Mars Rover "Opportunity". Solar power is relatively easy to install. But there are several problems [START_REF] Landis | Mars Solar Power[END_REF], including smaller yield and dust storms. Another solution would be to use plutonium-238 to produce electricity, which is used by the Mars Rover "Curiosity" [START_REF]Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) -Factsheet[END_REF].

Survival on Mars -A VR Experience

In order to convey the fact that living on Mars is probably very different to what many people think we implemented the VR experience "Survival on Mars".

As VR headset we used the Oculus Quest. It comes with two controllers, one for each hand. The controllers provide one joystick, two buttons, one trigger and one "grip" button. The experience was developed with the game engine "Unity" version 2019.2.13f1 [START_REF]Unity. Unity[END_REF]. All sounds either got downloaded from the royalty free music website soundbible.com [START_REF]Soundbible[END_REF] or are self-made. In the game there is also a robot voice which was generated on a website called onlinegenerator.com [START_REF]Onlinetonegenerator[END_REF] and then captured from there.

Main Story Line

To let the player dive into the scenario and leave an impression, it was necessary to create a story similar structured like a movie, encompassiung an introduction, a confrontation, and a climax.

The story begins on the main menu screen, where the player learns that a couple of months have passed since the first humans successfully landed on Mars. They live under the surface to keep safe from radiation. Regularly though, one of the astronauts has to get back up on to the surface and check the status there. The astronaut has to analyze the plants in the green house for toxic or non toxic plants, he has to collect stone probes that will get analyzed for water traces, and he has to make sure that the electricity is working.

The player slips into the role of one of those astronauts and the game starts. He wakes up in the main station, a base which provides several resources that the player will need later on. The astronaut has to go outside, this is the moment the player first experiences to be on the surface of Mars. He sees and hears a little breeze, and feels the harshness of the red planet. During the whole operation the player always has to have an eye on his left HUD, where he sees his oxygen and radiation status. If the oxygen runs out, the game is over, if the radiation is too high, the game is also over. He gets prompted the task to go to the green house and analyze the plants. The player walks in there and sees many different plants in there. On the other end of the room, there is a "Plant Analyzer", which allows the astronaut to check whether a plant is toxic or edible. He has to put the plants on there, then the analyzing process starts. After he finds an edible plant, he has to bring it to the main station. In the main station there is a "Radiation Defuser", which brings down the players radiation level.

After this, the player gets the task to go to the drilling station where he has to collect multiple stone probes. He does that and again has to return back to the main station.

Suddenly a voice tells him that he quickly has to get the power back on because the green house is in danger to freeze without heating. He rushes there and manages to get the power back on. A voice tells him that a sand storm is on the way and he has to get back to the main station as fast as possible. The player tries to get there. As the sand storm reaches the players location, he notices a drastic oxygen loss. This is where the game ends.

Description of Scenes

Title Screen: The first thing the player sees after the "Splash Screen" with the Unity Logo is the Title Screen. It features a great view of the red planet with the title "Survival On Mars" and a Start button. It is also the first time the player sees his "virtual hands". To navigate through this menu and press buttons, there is a ray attached to the right hand. It points from the hand to the canvas which holds the button and the text. After pressing start, while the next scene gets loaded in the background, there is a brief introduction to the backstory (cf. Section 4.1). Then the player can finally start the main scene.

Main Scene: After the title screen the player wakes up in the Main Base of the Main Scene. He gets prompted tasks to his HUD and explores the main compound (cf. Figure 4) consisting of the following sites:

-The Green House: (cf. Figure 1). The green house is a lab where different kinds of plants are cultured. A big problem of growing food on Mars, is that the soil is toxic due to Perchlorate [START_REF] Wadsworth | Perchlorates on Mars enhance the bacteriocidal effects of UV light[END_REF]. This is why the lab features a "Plant Analyzer" which analyzes if plants are toxic or not. -The Drilling Site: (cf. Figure 2). The drilling site is a place where a big drilling machine mines martian rocks to look for potential water resources. -The Solar Panels: (cf. Figure 3). The solar panels are responsible for the power supply of the whole mission.

Gameplay and Mechanics

To show the player all the information he needs to finish his tasks and also to add game mechanics, it was necessary to create a Head-Up-Display (HUD) system, in this case displayed at the player's left or right wrist. To display the current oxygen and radiation level (see below)the left wrist is equipped with two sliders, one for the radiation. To show the user what he is supposed to do the right wrist also got a HUD which always shows the current mission/goal. (cf. Figure 5) To make it easier for the player to fulfill the tasks and find their way, there are several highlighters set on the map which are switched on if the mission requires the user to do so, and switched back off when the player has arrived at the corresponding location.

One of the main interaction methods used in the experience are buttons (cf. Figure 6). To activate A button, the player does not have to press a button on the controller, but simply extend his index finger and move it towards the button until he pushes it.

Many objects in the experience can get grabbed by the player. For that, the user has to press the "grab button" or simply make a fist. By that, the grabbable object sticks to the hand and it can get moved/rotated in any direction. The feature of picking up objects is for example used when analyzing plants in the green house. As a gameplay element, the player has to always keep an eye on his oxygen and radiation level. If the oxygen runs out, or the radiation level hits the maximum, the game is over.

Missions and Challenges

The player basically has to fulfill three missions:

1. Analyzing the plants in the green house. The player has to get to the green house. Inside there is the "Plant Analyzer", a fictional machine which can specify if a plant is toxic or not. The user has to grab one of the plants and put it on the analyzer. If the display shows that the plant is edible, he has to take it with him and bring it back to the main base. 2. Collecting stone probes from the drilling site. Here the player has to collect at least 3 stone probes and bring them back to the main base. 3. Repairing the power generator at the solar panels. Since the plants located in the green house need a decent warm temperature, they are relying on the power supply from the solar panels. The player gets prompted that he must reactivate the power supply to save the plants. There is also a slider which indicates how much time the player has left.

Besides these 3 missions, the player always has to check his oxygen resources and radiation level. If the player is inside and the doors are closed, he does not loose oxygen and does not gain radiation. To defuse the radiation he can use the "Radiation Defuser" in the main base, but he can only use it once in the whole experience.

In a very early stage of the project, the only possible way for the player to switch his location was by "teleporting" to fixed positions. Later on, we decided that it would be better if the player can move around freely, since that provides more freedom. Unfortunately, this has the side effect of increasing the occurrence of motion sickness for some people.

Evaluation and Discussion

To see if the experience would have an effect on peoples perception of Mars, a couple of persons were asked to do a full play through of the game. Overall, 7 people participated: 4 men and 3 women. Their age ranged from 26 to 64. None of the participants had a scientific background, or special previous knowledge about the subject. In advance, the people were asked to answer a questionnaire. It consisted of basic statements about conditions on Mars, general perception of the red planet, as well as if they had ever experienced virtual reality before. The people had to say 'yes' or 'no', to state if their opinion matches with the statement or not: During the actual experience, they were introduced to the controls and got a pair of headphones to achieve a higher immersion. If the participants had problems to finish the tasks, they received a hint.

After they had finished the experience -either by loosing or by completing the game -they got a second questionnaire with the same questions, but without question nr. 7. It turned out, that everyone who was supporting Mars expeditions in the first place, did not change their opinion after the experience. Everyone who thought that Mars was a suitable alternative to Mars changed their opinion, although some mentioned that Mars was not the best, but "the only alternative" to earth. Every participant knew that it is impossible to survive without a space suit on the red planet, and also everyone knew that there is water on Mars.

However, none of the participants knew, that Mars has in fact a very thin atmosphere instead of a thick, and also did not know it after the experience. Only a few were correct about the drastic temperature differences on Mars, everyone knew it after the experience. Every participant learned about the toxic soil and the radiation in the experience.

Overall the participants did well in fulfilling the prompted tasks. Unfortunately, some of the players suffered from motion sickness during the experience, and one of them even had to stop because of this. Another point of criticism was the lack of action or music.

Conclusions and Future Work

The results clearly show that "Survival On Mars" has an effect on peoples perception on Mars. For future work, a revision of the existing game with a more focused approach on entertainment would probably be beneficial of the overall experience and could also lead to a much greater impact on peoples opinions.

Even though the experience raised awareness about how hostile Mars is, the desire to settle Mars, still is -such as the general wish to explore the universedeep embedded in our society and will probably remain there.

Figure 1 . 2 .Figure 3 . 4 .

 1234 Figure 1. Inside the Green House Figure 2. The Drilling Site

Figure 5 . 6 .

 56 Figure 5. The left and the right HUD Figure 6. Some buttons.

  1. "I support attempts to land astronauts on Mars." 2. "Mars is a suitable alternative to Earth for humankind." 3. "It is possible to survive on Mars without a space suit." 4. "There are water resources on Mars." 5. "Temperatures on Mars' surface are similar to Earths' surface." 6. "Just like Earth, Mars has a thick atmosphere." 7. "I have tried virtual reality before."