52 resultados para Nintendo games


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We consider the behaviour of a set of services in a stressed web environment where performance patterns may be difficult to predict. In stressed environments the performances of some providers may degrade while the performances of others, with elastic resources, may improve. The allocation of web-based providers to users (brokering) is modelled by a strategic non-cooperative angel-daemon game with risk profiles. A risk profile specifies a bound on the number of unreliable service providers within an environment without identifying the names of these providers. Risk profiles offer a means of analysing the behaviour of broker agents which allocate service providers to users. A Nash equilibrium is a fixed point of such a game in which no user can locally improve their choice of provider – thus, a Nash equilibrium is a viable solution to the provider/user allocation problem. Angel daemon games provide a means of reasoning about stressed environments and offer the possibility of designing brokers using risk profiles and Nash equilibria.

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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.