49 resultados para C72 - Noncooperative Games


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We analyze ways by which people decompose into groups in distributed systems. We are interested in systems in which an agent can increase its utility by connecting to other agents, but must also pay a cost that increases with the size of the sys- tem. The right balance is achieved by the right size group of agents. We formulate and analyze three intuitive and realistic games and show how simple changes in the protocol can dras- tically improve the price of anarchy of these games. In partic- ular, we identify two important properties for a low price of anarchy: agreement in joining the system, and the possibil- ity of appealing a rejection from a system. We show that the latter property is especially important if there are some pre- existing constraints regarding who may collaborate (or com- municate) with whom.

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Cognitive assessment typically involves assessing a person’s cognitive performance in unfamiliar and ar-guably unnatural clinical surroundings. User-centred approaches to assessment and monitoring, driven by issues such as enjoyability and familiarity, are largely absent. Everyday technologies, for example, smartphones represent an opportunity to obtain an objective assessment of a person’s cognitive capabili-ties in a non-threatening, discreet and familiar way, e.g. by everyday puzzle games undertaken as a leisure activity at home. We examined the strength of relationships that exist between performance on common puzzle games and standard measures of neuropsychological performance. Twenty-nine participants, aged 50 - 65 years, completed a comprehensive neuropsychological test battery and played three smart-phone-based puzzle games in triplicate: a picture puzzle [Matches Plus], a word puzzle [Jumbline] and a number puzzle [Sudoku]. As anticipated, a priori, significant correlations were observed between scores on a picture puzzle and visual memory test (r = 0.49; p = 0.007); a word puzzle and estimated verbal IQ (r = 0.53; p = 0.003) and verbal learning (r = 0.30; p = 0.039) tests; and a number puzzle and reason-ing/problem solving test (r = 0.42; p = 0.023). Further analyses making allowance for multiple compari-sons identified a significant unanticipated correlation (r = 0.49; p = 0.007) between number puzzle scores and a measure of nonverbal working memory. Performance on these smartphone-based games was in-dicative of relative cognitive ability across several cognitive domains at a fixed time point. Smart-phone-based, everyday puzzle games may offer a valid, portable measure of assessing and monitoring cognition in older adults.

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This chapter explores the nature of “learning” in games-based learning and the cognitive and motivational processes that might underpin that learning by drawing on psychological theories and perspectives. Firstly, changing conceptions of learning over the last few decades are reviewed. This is described in relation to the changes in formal learning theories and connections made between learning theory and GBL. Secondly, the chapter reviews empirical research on the learning outcomes that have been identified for GBL, with specific focus on cognitive benefits, school attainment, collaborative working, and the motivational and engaging appeal of games. Finally, an overview of the dominant theoretical perspectives/findings mostly associated with GBL is presented in an attempt to broaden understanding of the potential for GBL in the classroom.

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We propose an allocation rule that takes into account the importance of both players and their links and characterize it for a fixed network. Our characterization is along the lines of the characterization of the Position value for Network games by van den Nouweland and Slikker (2012). The allocation rule so defined admits multilateral interactions among the players through their links which distinguishes it from the other existing rules. Next, we extend our allocation rule to flexible networks à la Jackson (2005).

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The research presented in this paper proposes a set of design guidelines in the context of a Parkinson's Disease (PD) rehabilitation design framework for the development of serious games for the physical therapy of people with PD. The game design guidelines provided in the paper are informed by the study of the literature review and lessons learned from the pilot testing of serious games designed to suit the requirements of rehabilitation of patients with Parkinson's Disease. The proposed PD rehabilitation design framework employed for the games pilot testing utilises a low-cost, customized and off-the-shelf motion capture system (employing commercial game controllers) developed to cater for the unique requirement of the physical therapy of people with PD. Although design guidelines have been proposed before for the design of serious games in health, this is the first research paper to present guidelines for the design of serious games specifically for PD motor rehabilitation.

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The main purpose of this study is to determine the game principles that need to be adopted in order to create an enjoyable and engaging game experience for older adults, whilst ensuring that the purpose of the game, encouraging upper limb mobility, is respected. The study reported in this paper involved a group of older adults who played and gave feedback on an early game prototype which feed into the design modification process. Each player's action capabilities were measured and taken into account in the design process. This helped ensure that opportunities for action that the game afforded were adapted to players' need.

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Boolean games are a framework for reasoning about the rational behavior of agents whose goals are formalized using propositional formulas. Compared to normal form games, a well-studied and related game framework, Boolean games allow for an intuitive and more compact representation of the agents’ goals. So far, Boolean games have been mainly studied in the literature from the Knowledge Representation perspective, and less attention has been paid on the algorithmic issues underlying the computation of solution concepts. Although some suggestions for solving specific classes of Boolean games have been made in the literature, there is currently no work available on the practical performance. In this paper, we propose the first technique to solve general Boolean games that does not require an exponential translation to normal-form games. Our method is based on disjunctive answer set programming and computes solutions (equilibria) of arbitrary Boolean games. It can be applied to a wide variety of solution concepts, and can naturally deal with extensions of Boolean games such as constraints and costs. We present detailed experimental results in which we compare the proposed method against a number of existing methods for solving specific classes of Boolean games, as well as adaptations of methods that were initially designed for normal-form games. We found that the heuristic methods that do not require all payoff matrix entries performed well for smaller Boolean games, while our ASP based technique is faster when the problem instances have a higher number of agents or action variables.

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Boolean games are a framework for reasoning about the rational behaviour of agents, whose goals are formalized using propositional formulas. They offer an attractive alternative to normal-form games, because they allow for a more intuitive and more compact encoding. Unfortunately, however, there is currently no general, tailor-made method available to compute the equilibria of Boolean games. In this paper, we introduce a method for finding the pure Nash equilibria based on disjunctive answer set programming. Our method is furthermore capable of finding the core elements and the Pareto optimal equilibria, and can easily be modified to support other forms of optimality, thanks to the declarative nature of disjunctive answer set programming. Experimental results clearly demonstrate the effectiveness of the proposed method.

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In Boolean games, agents try to reach a goal formulated as a Boolean formula. These games are attractive because of their compact representations. However, few methods are available to compute the solutions and they are either limited or do not take privacy or communication concerns into account. In this paper we propose the use of an algorithm related to reinforcement learning to address this problem. Our method is decentralized in the sense that agents try to achieve their goals without knowledge of the other agents’ goals. We prove that this is a sound method to compute a Pareto optimal pure Nash equilibrium for an interesting class of Boolean games. Experimental results are used to investigate the performance of the algorithm.

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This paper investigates the profile of teachers in the island of Ireland who declared themselves willing to undertake professional development activities in programming, in particular to master programming by taking on-line courses involving the design of computer games. Using the Technology Acceptance Model (TAM), it compares scores for teachers “willing” to undertake the courses with scores for those who declined, and examines other differences between the groups of respondents. Findings reflect the perceived difficulties of programming and the current low status accorded to the subject in Ireland. The paper also reviews the use of games-based learning as a “hook” to engage learners in programming and discusses the role of gamification as a tool for motivating learners in an on-line course. The on-line course focusing on games design was met with enthusiasm, and there was general consensus that gamification was appropriate for motivating learners in structured courses such as those provided.