Explaining how to play real-time strategy games

Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End-user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior

Risk Dominance Selects the Leader: An Experimental Analysis

We perform an experimental analysis to test whether the risk dominance prediction is supported by the behavior of laboratory agents, in a 2X 2 coordination game whose equilibria are not Pareto ranked. This type of game arises very often in studies of industrial organization and international trade, and we extract the parameters for the experiment from a vertical product differentiation model with two asymmetric players choosing first qualities and then prices.We show that the higher the degree of asymmetry of the game, the higher the predictive power of the risk dominance criterion.Publicad

The things we learned on Liberty Island: designing games to help people become competent game players

The growing interest in the relationship between games and learning has, to date, be dominated by two traditions of work. The first treats games as potential educational content; the second considers the social contexts of learning from games, but only at a general level. A methodology has been developed that permits the detailed analysis of how people learn from particular instances of game play. This approach is used here to study two approaches to playing Deus Ex, one involving the training level and one neglecting this. The analysis revealed the things players learnt, the strategies they developed to progress through the game, the way in which these strategies evolved and also the way in which previous experience was transferred to this new context of play. This analysis permits conclusions to be drawn about the value of training levels and the importance of designing games in a way that recognizes previous gaming experience. The analysis also has implications for defining game genres, for decisions about the inclusion of design features such as quick saves and for the design of AI scripts

Unmasking Clever Hans Predictors and Assessing What Machines Really Learn

Current learning machines have successfully solved hard application problems, reaching high accuracy and displaying seemingly "intelligent" behavior. Here we apply recent techniques for explaining decisions of state-of-the-art learning machines and analyze various tasks from computer vision and arcade games. This showcases a spectrum of problem-solving behaviors ranging from naive and short-sighted, to well-informed and strategic. We observe that standard performance evaluation metrics can be oblivious to distinguishing these diverse problem solving behaviors. Furthermore, we propose our semi-automated Spectral Relevance Analysis that provides a practically effective way of characterizing and validating the behavior of nonlinear learning machines. This helps to assess whether a learned model indeed delivers reliably for the problem that it was conceived for. Furthermore, our work intends to add a voice of caution to the ongoing excitement about machine intelligence and pledges to evaluate and judge some of these recent successes in a more nuanced manner.Comment: Accepted for publication in Nature Communication

Demystifying the educational benefits of different gaming genres

As research continues into the use of computer games for educational purposes, educators still appear reluctant to incorporate them into their teaching. One contributing factor to this reluctance is the lack of information regarding the benefits offered by the different games available today. These differences appear to have been largely overlooked by the academic community, resulting in a lack of information being made available to both the academic and education communities alike. Without this information, educators will find it difficult to determine whether a game will suit their teaching needs, and will continue to avoid using them. This paper studies a selection of games from several different genres, assessing each one in its ability to fulfil a set of previously identified requirements for a good educational resource. The results of the investigation showed that there were indeed strong differences between the genres, allowing for some suggestions to be made regarding their use in education, as well as leaving room for some interesting future work

Demystifying the Educational Benefits of Different Gaming Genres

As research continues into the use of computer games for educational purposes, educators still appear reluctant to incorporate them into their teaching. One contributing factor to this reluctance is the lack of information regarding the benefits offered by the different games available today. These differences appear to have been largely overlooked by the academic community, resulting in a lack of information being made available to both the academic and education communities alike. Without this information, educators will find it difficult to determine whether a game will suit their teaching needs, and will continue to avoid using them. This paper studies a selection of games from several different genres, assessing each one in its ability to fulfil a set of previously identified requirements for a good educational resource. The results of the investigation showed that there were indeed strong differences between the genres, allowing for some suggestions to be made regarding their use in education, as well as leaving room for some interesting future work

(WP 2010-08) Neuroeconomics: Constructing Identity

This paper asks whether neuroeconomics will make instrumental use of neuroscience to adjudicate existing disputes in economics or be more seriously informed by neuroscience in ways that might transform economics. The paper pursues the question by asking how neuroscience constructs an understanding of individuals as whole persons. The body of the paper is devoted to examining two approaches: Don Ross’s neurocellular approach to neuroeconomics and Joseph Dumit’s cultural anthropological science organization approach. The accounts are used to identify boundaries on single individual explanations. With that space Andy Clark’s external scaffolding view and Nathaniel Wilcox’s socially distributed cognition view are employed

Testing Game Theory in the Field: Swedish LUPI Lottery Games

Game theory is usually difficult to test precisely in the field because predictions typically depend sensitively on features that are not controlled or observed. We conduct one such test using field data from the Swedish lowest unique positive integer (LUPI) game. In the LUPI game, players pick positive integers and whoever chose the lowest unique number wins a fixed prize. Theoretical equilibrium predictions are derived assuming Poisson- distributed uncertainty about the number of players, and tested using both field and laboratory data. The field and lab data show similar patterns. Despite various deviations from equilibrium, there is a surprising degree of convergence toward equilibrium. Some of the deviations from equilibrium can be rationalized by a cognitive hierarchy model