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From the abstract: "Collective Artificial Intelligence (CAI) simulates human intelligence from data contributed by many humans, mined for inter-related patterns. This thesis applies CAI to social role-playing, introducing an end-to-end process for compositing recorded performances from thousands of humans, and simulating open-ended interaction from this data. The CAI process combines crowdsourcing, pattern discovery, and case-based planning. Content creation is crowdsourced by recording role-players online. Browser-based tools allow non-experts to annotate data, organizing content into a hierarchical narrative structure. Patterns discovered from data power a novel system combining plan recognition with case-based planning. The combination of this process and structure produces a new medium, which exploits a massive corpus to realize characters who interact and converse with humans. This medium enables new experiences in videogames, and new classes of training simulations, therapeutic applications, and social robots. .... As a proof of concept, a CAI system has been evaluated by recording over 10,000 performances in The Restaurant Game, automating an AI-controlled waitress who interacts in the world, and converses with a human via text or speech. Quantitative results demonstrate CAI supports significantly open-ended interaction with humans, while focus groups reveal factors for improving engagement."

Abstract: "Player metrics are an invaluable resource for game designers and QA analysts who wish to understand players, monitor and improve game play, and test design hypotheses. Usually such metrics are collected in a straightforward manner by passively recording players; however, such an approach has several potential drawbacks. First, passive recording might fail to record metrics which correspond to an infrequent player behavior. Secondly, passive recording can be a costly, laborious, and memory intensive process, even with the aid of tools. In this paper, we explore the potential for an active approach to player metric collection which strives to collect data more efficiently, and thus with less cost. We use an online, iterative approach which models the relationship between player metrics and in-game situations probabilistically using a Markov Decision Process (MDP) and solves it for the best game configurations to run. To analyze the benefits and limitations of this approach, we implemented a system, called GAMELAB, for recording player metrics in Second Life."

Abstract: "This paper proposes a new framework for automated analysis of game-play metrics for aiding game designers in nding out the critical aspects of the game caused by factors like design modications, change in playing style, etc. The core of the algorithm measures similarity between spatial distribution of user generated in-game events and automatically ranks them in order of importance. The feasibility of the method is demonstrated on a data set collected from a modern, multiplayer First Person Shooter, together with application examples of its use. The proposed framework can be used to accompany traditional testing tools and make the game design process more efficient."

Abstract: "ARTigo is a Game with a Purpose platform whose goal is to collect tags for artworks, which can be used for retrieval. The ARTigo gam es form a tagging ecosystem, where the games cooperate in order to gather a wide range of information. Description games create initial tags, in order to enable other games to be played and collect semantically shallow surface tags. Dissemination games sp read existing data to other artworks or languages, and do not create new information. Diversification games feed on data produced by other games and guide the players to entering more specific tags. Finally, integration games create higher - order tags with deep semantic meanings, describing emotions for example. All these different types of tags have different semantic depths, and are present in different quantities. Together, they create a pool of complementary tags accurately describing artworks, which can be processed for data mining."

Abstract: "A recent trend within computational intelligence and games research is to investigate how to affect video game players' in-game experience by designing and/or modifying aspects of game content. Analysing the relationship between game content, player behaviour and self-reported affective states constitutes an important step towards understanding game experience and constructing effective game adaptation mechanisms. This papers reports on further refinement of a method to understand this relationship by analysing data collected from players, building models that predict player experience and analysing what features of game and player data predict player affect best. We analyse data from players playing 780 pairs of short game sessions of the platform game Super Mario Bros, investigate the impact of the session size and what part of the level that has the major affect on player experience. Several types of features are explored, including item frequencies and patterns extracted through frequent sequence mining."

Abstract: "In this paper, we describe a methodology for capturing player experience while interacting with a game and we present a data-driven approach for modeling this interaction. We believe the best way to adapt games to a specic player is to use quantitative models of player ex- perience derived from the in-game interaction. Therefore, we rely on crowd-sourced data collected about game context, players behavior and players self-reports of dierent aective states. Based on this informa- tion, we construct estimators of player experience using neuroevolution- ary preference learning. We present the experimental setup and the re- sults obtained from a recent case study where accurate estimators were constructed based on information collected from players playing a rst- person shooter game. The framework presented is part of a bigger picture where the generated models are utilized to tailor content generation to particular player's needs and playing characteristics."

Abstract: "This paper describes the design and evaluation of Zoo U, a novel computer game to assess children's social skills development. Zoo U is an innovative product that combines theory-driven content and customized game mechanics. The game-like play creates the opportunity for stealth assessment, in which dynamic evidence of social skills is collected in real time and players' choices during gameplay provide the needed data. To ensure the development of an engaging and valid game, we utilized an iterative datadriven validation process in which the game was created, tested, revised based on student performance and feedback, and retested until game play was statistically matched to independent ratings of social skills. We first investigated whether the data collected through extensive logging of student actions provided information that could be used to improve the assessment. We found that detailed game logs of socially relevant player behavior combined with external measures of player social skills provided an efficient vector to incrementally improve the accuracy of the embedded assessments. Next, we investigated whether the game performance correlated with teachers' assessments of students' social skills competencies. An evaluation of the final game showed (a) significant correlations between in-game social skills assessments and independently obtained standard psychological assessments of the same students and (b) high levels of engagement and likeability for students. These findings support the use of the interactive and engaging computer game format for the stealth assessment of children's social skills. The created innovative design methodologies should prove useful in the design and improvement of computer games in education."

"The U.S. government has hired a California-based company to hack into video game consoles, such as Xbox 360 and PlayStation 3, to watch criminals, especially child predators, and learn how to collect evidence against them."

Abstract: "Through the use of an online discussion, this study collected the detailed perspectives of 29 'hardcore' and 'casual' gamers, regarding the topic of FPS video games. It investigates what the gamers want in a FPS by means of an online discussion which builds on the benefits of both ethnography and focus group methodologies. Since the study's main goal was exploratory, a qualitative approach was considered the most appropriate; in addition to this, the method used to collect the data was done within a grounded theory framework. This study finds that, though graphics have historically been a major factor in driving the success of a FPS video game, this is no longer the case. Gamers expect there to be a balance between the different components, with a more holistic gaming experience desired, and that too much focus on one component at the expense of another will result in an unsatisfactory video game experience. This can be seen in comments given by the participants indicating too much emphasis of the graphics quality in a FPS and not enough on story or the multiplayer aspects results in a video game which is neither fun nor praiseworthy. The latter is perceived significant as with such an oversaturation in the video game market, developers rely heavily on positive word of mouth to advertise their games. This study's main goal was to develop a better understanding of the expectations of gamers regarding FPS; in doing so, it has laid out the basis for producing a 'magic formula' for a great FPS video game. It has also highlighted several other areas which need further investigation in order to better understand the behavioural motives and actions of gamers from both 'hardcore' and 'casual' communities."

Abstract: "This literature review describes gamification and how it can be used in a crowdsour cing context. It relates motivations for participating in such activity as more intrinsic than conventional methods, and as such provides numerous benefits. Such benefits include more accurate work, better retention rates, and a more cost effective solutio n. Elements of gamification are examined, as well as how it can be applied to existing applications."

Abstract: "Citizen science is a form of social computation where members of the public are recruited to contribute to scientific investigations. Citizen-science projects often use web-based systems to support collaborative scientific activities, making them a form of computer-supported cooperative work. However, finding ways to attract participants and confirm the veracity of the data they produce are key issues in making such systems successful. We describe a series of web-based tools and games currently under development to support taxonomic classification of organisms in photographs collected by citizen-science projects. In the design science tradition, the systems are purpose-built to test hypotheses about participant motivation and techniques for ensuring data quality. Findings from preliminary evaluation and the design process itself are discussed."

Abstract: "We present a case study in the design of an educational video game about collecting, curating, and museum operations. A five-step cyclic design thinking framework was used by the studio during the design and development of the game, and the team was simultaneously the subject of a rigorous and detailed ethnographic study. Three stages of the game's design evolution are presented through the lens of the design thinking framework. The team's practice-based research is tri- angulated with our empirical data to produce four key findings: (a) that empathy for learning context is critical in aligning designs with learning objectives; (b) that meeting with stakeholders spurs empathy-building; (c) that there is a tension between horizontal and vertical slicing that is revealed by design thinking processes; and (d) that iterative design processes challenge conventions of higher education."

Abstract: "The purpose of this study aimed to construct an online competitive game-based learning system by using freeware for junior high school students and to assess its effectiveness. From the learning standpoints, game mechanisms including learning points, competition mechanism, training room mechanism, questioning & answering mechanism, tips, and feedback mechanism are taken into consideration while constructing the system. The system contains screens of Log-in, Game lobby, Waiting room, Player's room, Question & Answer, and Scoring. After the system was established, it was implemented in a 10 week teaching experiment. A total of 35 junior high school students participated in this teaching experiment. Both pre-test and post-test were administered and analyzed. A 5-point Likert scale questionnaire, containing domains of system operation, learning effectiveness, competition and incentive, and training room learning was also included to assess user's satisfaction. Descriptive analysis and independent t test were used to analyze the collected data. The findings of the study show that most students are satisfied with the four domains of the freeware constructed online competitive game-based learning system. Meanwhile, the online competitive game-based learning system is effective for junior high school students' learning."

"In the game, the player acts out the role of a conservator, conservation scientist or collection manager by virtually interacting with objects, materials and data embedded in quest narratives. Within the game, players will be allowed to manage a library and protect it from the elements that accelerate deterioration. Another quest will allow players to take samples from ancient artifacts and analyze them to discover the secrets of its past."