Forming Probably Stable Communities with Limited Interactions

A community needs to be partitioned into disjoint groups; each community member has an underlying preference over the groups that they would want to be a member of. We are interested in finding a stable community structure: one where no subset of members $S$ wants to deviate from the current structure. We model this setting as a hedonic game, where players are connected by an underlying interaction network, and can only consider joining groups that are connected subgraphs of the underlying graph. We analyze the relation between network structure, and one's capability to infer statistically stable (also known as PAC stable) player partitions from data. We show that when the interaction network is a forest, one can efficiently infer PAC stable coalition structures. Furthermore, when the underlying interaction graph is not a forest, efficient PAC stabilizability is no longer achievable. Thus, our results completely characterize when one can leverage the underlying graph structure in order to compute PAC stable outcomes for hedonic games. Finally, given an unknown underlying interaction network, we show that it is NP-hard to decide whether there exists a forest consistent with data samples from the network.Comment: 11 pages, full version of accepted AAAI-19 pape

Glitchspace:teaching programming through puzzles in cyberspace

There is an increasing need to address the player experience in games-based learning. Whilst games offer enormous potential as learning experiences, the balance between entertainment and education must be carefully designed and delivered. Successful commercial games tend to focus gameplay above any educational aspects. In contrast, games designed for educational purposes have a habit of sacrificing entertainment for educational value which can result in a decline in player engagement. For both, the player experience is critical as it can have a profound effect on both the commercial success of the game and in delivering the educational engagement. As part of an Interface-funded research project Abertay University worked with the independent games company, Space Budgie, to enhance the user experience of their educational game Glitchspace. The game aimed to teach basic coding principles and terminology in an entertaining way. The game sets the player inside a Mondrian-inspired cyberspace world where to progress the player needs to reprogramme the world around them to solve puzzles. The main objective of the academic-industry collaborative project was to analyse the user experience (UX) of the game to increase its educational value for a standalone educational version. The UX design focused on both pragmatic and hedonic qualities such playability, usability and the psychological impact of the game. The empirical study of the UX design allowed all parties to develop a deeper understanding of how the game was being played and the initial reactions to the game by the player. The core research question that the study sought to answer was whether when designing an educational game, UX design could improve philosophical concepts like motivation and engagement to foster better learning experiences.</p

Optimal Partitions in Additively Separable Hedonic Games

We conduct a computational analysis of fair and optimal partitions in additively separable hedonic games. We show that, for strict preferences, a Pareto optimal partition can be found in polynomial time while verifying whether a given partition is Pareto optimal is coNP-complete, even when preferences are symmetric and strict. Moreover, computing a partition with maximum egalitarian or utilitarian social welfare or one which is both Pareto optimal and individually rational is NP-hard. We also prove that checking whether there exists a partition which is both Pareto optimal and envy-free is $\Sigma_{2}^{p}$-complete. Even though an envy-free partition and a Nash stable partition are both guaranteed to exist for symmetric preferences, checking whether there exists a partition which is both envy-free and Nash stable is NP-complete.Comment: 11 pages; A preliminary version of this work was invited for presentation in the session `Cooperative Games and Combinatorial Optimization' at the 24th European Conference on Operational Research (EURO 2010) in Lisbo

Strategyproof Mechanisms for Additively Separable Hedonic Games and Fractional Hedonic Games

Additively separable hedonic games and fractional hedonic games have received considerable attention. They are coalition forming games of selfish agents based on their mutual preferences. Most of the work in the literature characterizes the existence and structure of stable outcomes (i.e., partitions in coalitions), assuming that preferences are given. However, there is little discussion on this assumption. In fact, agents receive different utilities if they belong to different partitions, and thus it is natural for them to declare their preferences strategically in order to maximize their benefit. In this paper we consider strategyproof mechanisms for additively separable hedonic games and fractional hedonic games, that is, partitioning methods without payments such that utility maximizing agents have no incentive to lie about their true preferences. We focus on social welfare maximization and provide several lower and upper bounds on the performance achievable by strategyproof mechanisms for general and specific additive functions. In most of the cases we provide tight or asymptotically tight results. All our mechanisms are simple and can be computed in polynomial time. Moreover, all the lower bounds are unconditional, that is, they do not rely on any computational or complexity assumptions

Analysing the Role of Interactivity in User Experience

An experimental investigation into the role of interaction in user experience (UX) with a controlled manipulation of interactivity features (e.g. avatars, interactive video) in a university information website is reported. The more interactive version had better affect and hedonic ratings, even though its perceived usability was worse. Analysis of qualitative data showed users were attracted to the interactive features, although they complained about poor usability. The results of the experiments are discussed to consider the role of interactivity in user experience and the differences between users’ quantitative judgements of UX and their comments on interactive features which reveal different perspectives

Multi-agent Learning For Game-theoretical Problems

Multi-agent systems are prevalent in the real world in various domains. In many multi-agent systems, interaction among agents is inevitable, and cooperation in some form is needed among agents to deal with the task at hand. We model the type of multi-agent systems where autonomous agents inhabit an environment with no global control or global knowledge, decentralized in the true sense. In particular, we consider game-theoretical problems such as the hedonic coalition formation games, matching problems, and Cournot games. We propose novel decentralized learning and multi-agent reinforcement learning approaches to train agents in learning behaviors and adapting to the environments. We use game-theoretic evaluation criteria such as optimality, stability, and resulting equilibria