998 resultados para evolutionary games


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This study explores the idea of video games where the players are not just allowed to express themselves creatively, but are challenged to do so and are judged based on the quality of their creative expression. The outcome of the research is a series of six games which comment on this idea. The study also raises further questions regarding how current video games are constructed and designed in comparison with non-computer games, and invites a further evolution of the craft of video game design in a direction that focuses more on interpreting and reacting to what the player is doing.

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The "Humies" awards are an annual competition held in conjunction with the Genetic and Evolutionary Computation Conference (GECCO), in which cash prizes totalling $10,000 are awarded to the most human-competitive results produced by any form of evolutionary computation published in the previous year. This article describes the gold medal-winning entry from the 2012 "Humies" competition, based on the LUDI system for playing, evaluating and creating new board games. LUDI was able to demonstrate human-competitive results in evolving novel board games that have gone on to be commercially published, one of which, Yavalath, has been ranked in the top 2.5% of abstract board games ever invented. Further evidence of human-competitiveness was demonstrated in the evolved games implicitly capturing several principles of good game design, outperforming human designers in at least one case, and going on to inspire a new sub-genre of games.

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Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with civil aircraft and UAV, UCAV systems are implemented numerically and discussed. Applications of increasing optimization complexity are presented as well as two hands-on test cases problems. These examples focus on aeronautical applications and will be useful to the practitioner in the laboratory or in industrial design environments. The evolutionary methods coupled with games presented in this volume can be applied to other areas including surface and marine transport, structures, biomedical engineering, renewable energy and environmental problems.

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Technological system evolution is marked by the uneven evolution of constituent sub-systems. Subsequently, system evolution is hampered by the resulting state of unevenness, or reverse salience, which results from the presence of the sub-system that delivers the lowest level of performance with respect to other sub-systems, namely, the reverse salient. In this paper, we develop absolute and proportional performance gap measures of reverse salience and, in turn, derive a typology of reverse salients that distinguishes alternative dynamics of change in the evolving system. We subsequently demonstrate the applicability of the measures and the typology through an illustrative empirical study of the PC (personal computer) technological system that functions as a gaming platform. Our empirical analysis demonstrates that patterns of temporal dynamics can be distinguished with the measurement of reverse salience, and that distinct paths of technological system evolution can be identified as different types of reverse salients emerge over time.

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Binmore and Samuelson (1999) have shown that perturbations (drift) are crucial to study the stability properties of Nash equilibria. We contribute to this literature by providing a behavioural foundation for models of evolutionary drift. In particular, this article introduces a microeconomic model of drift based on the similarity theory developed by Tversky (1977), Kahneman and Tversky (1979) and Rubinstein (1988),(1998). An innovation with respect to those works is that we deal with similarity relations that are derived from the perception that each agent has about how well he is playing the game. In addition, the similarity relations are adapted to a dynamic setting. We obtain different models of drift depending on how we model the agent´s assessment of his behaviour in the game. The examples of the ultimatum game and the chain-store game are used to show the conditions for each model to stabilize elements in the component of Nash equilibria that are not subgame- perfect. It is also shown how some models approximate the laboratory data about those games while others match the data.

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In an evolutionary model, players from a given population meet randomly in pairs each instant to play a coordination game. At each instant, the learning model used is determined via some replicator dynamics that respects payoff fitness. We allow for two such models: a belief-based best-response model that uses a costly predictor, and a costless reinforcement-based one. This generates dynamics over the choice of learning models and the consequent choices of endogenous variables. We report conditions under which the long run outcomes are efficient (or inefficient) and they support the exclusive use of either of the models (or their co-existence).

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We demonstrate generating complete and playable card games using evolutionary algorithms. Card games are represented in a previously devised card game description language, a context-free grammar. The syntax of this language allows us to use grammar-guided genetic programming. Candidate card games are evaluated through a cascading evaluation function, a multi-step process where games with undesired properties are progressively weeded out. Three representa- tive examples of generated games are analysed. We observed that these games are reasonably balanced and have skill ele- ments, they are not yet entertaining for human players. The particular shortcomings of the examples are discussed in re- gard to the generative process to be able to generate quality games

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The evolutionary stability of cooperation is a problem of fundamental importance for the biological and social sciences. Different claims have been made about this issue: whereas Axelrod and Hamilton's [Axelrod, R. & Hamilton, W. (1981) Science 211, 1390-1398] widely recognized conclusion is that cooperative rules such as "tit for tat" are evolutionarily stable strategies in the iterated prisoner's dilemma (IPD), Boyd and Lorberbaum [Boyd, R. & Lorberbaum, J. (1987) Nature (London) 327, 58-59] have claimed that no pure strategy is evolutionarily stable in this game. Here we explain why these claims are not contradictory by showing in what sense strategies in the IPD can and cannot be stable and by creating a conceptual framework that yields the type of evolutionary stability attainable in the IPD and in repeated games in general. Having established the relevant concept of stability, we report theorems on some basic properties of strategies that are stable in this sense. We first show that the IPD has "too many" such strategies, so that being stable does not discriminate among behavioral rules. Stable strategies differ, however, on a property that is crucial for their evolutionary survival--the size of the invasion they can resist. This property can be interpreted as a strategy's evolutionary robustness. Conditionally cooperative strategies such as tit for tat are the most robust. Cooperative behavior supported by these strategies is the most robust evolutionary equilibrium: the easiest to attain, and the hardest to disrupt.

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Pac-Man is a well-known, real-time computer game that provides an interesting platform for research. We describe an initial approach to developing an artificial agent that replaces the human to play a simplified version of Pac-Man. The agent is specified as a simple finite state machine and ruleset. with parameters that control the probability of movement by the agent given the constraints of the maze at some instant of time. In contrast to previous approaches, the agent represents a dynamic strategy for playing Pac-Man, rather than a pre-programmed maze-solving method. The agent adaptively "learns" through the application of population-based incremental learning (PBIL) to adjust the agents' parameters. Experimental results are presented that give insight into some of the complexities of the game, as well as highlighting the limitations and difficulties of the representation of the agent.

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This volume explores sports mega-events, their social, political, and cultural characters, the value systems that they inscribe and draw on, the claims they make on us and the claims the organisers make for them, the spatial and ethical relationships they create, and the responses of civil societies to them. Our premise is that sports mega-events are not simply sporting or cultural phenomena. They are also political and economic events, characterised by the generation and projection of symbolic meanings – most obviously over the nature of statehood, economic power, and of collective cultural identity – and by social conflict, especially over land use, and over the extent and contours of public spending commitments. Because of their peculiar spatial and temporal organization, they raise questions about the relationships between global cultural and economic flows and particular local and national spaces. Because of their evolutionary characteristics, they ask us to consider not simply the time of the event but of the effects of the event on the long-term direction, implementation, and consequences of public policy.

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