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GECCO
2003
Springer
133views Optimization» more  GECCO 2003»
15 years 9 months ago
Dynamic Strategies in a Real-Time Strategy Game
Abstract. Most modern real-time strategy computer games have a sophisticated but fixed ‘AI’ component that controls the computer’s actions. Once the user has learned how suc...
William Joseph Falke II, Peter Ross
ATAL
2008
Springer
15 years 6 months ago
Strategic betting for competitive agents
In many multiagent settings, each agent's goal is to come out ahead of the other agents on some metric, such as the currency obtained by the agent. In such settings, it is no...
Liad Wagman, Vincent Conitzer
ATAL
2007
Springer
15 years 10 months ago
Reducing the complexity of multiagent reinforcement learning
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Andriy Burkov, Brahim Chaib-draa
ICANN
2005
Springer
15 years 9 months ago
Evolution of Heuristics for Give-Away Checkers
The efficacy of two evolutionary approaches to the problem of generation of heuristical linear and non-linear evaluation functions in the game of give-away checkers is tested in th...
Magdalena Kusiak, Karol Waledzik, Jacek Mandziuk
IUI
2004
ACM
15 years 9 months ago
Qualitative physics in virtual environments
In this paper, we describe a new approach to the creation of virtual environments, which uses qualitative physics to implement object behaviour. We adopted Qualitative Process The...
Marc Cavazza, Simon Hartley, Jean-Luc Lugrin, Mika...