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252,924
Playing stochastic games precisely
, 2012
"... Abstract. We study stochastic two-player games where the goal of one player is to achieve precisely a given expected value of the objective function, while the goal of the opponent is the opposite. Potential applications for such games include controller synthesis problems where the optimisation obj ..."
Abstract
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Cited by 3 (3 self)
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Abstract. We study stochastic two-player games where the goal of one player is to achieve precisely a given expected value of the objective function, while the goal of the opponent is the opposite. Potential applications for such games include controller synthesis problems where the optimisation
Two-player games: a reduction
, 2001
"... The goal of this chapter, together with the next one, is to give a detailed overview of the proof of the following result. Theorem 1 Let Γ be a two-player stochastic game with Þnite action and states sets. The game Γ has a uniform equilibrium payoff. The complete proof is to be found in Vieille [4], ..."
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The goal of this chapter, together with the next one, is to give a detailed overview of the proof of the following result. Theorem 1 Let Γ be a two-player stochastic game with Þnite action and states sets. The game Γ has a uniform equilibrium payoff. The complete proof is to be found in Vieille [4
Fractional Combinatorial Two-player Games
, 2013
"... During the last decades, many combinatorial games involving two persons playing on a (directed) graph have received a lot of attention. Some examples of such games are the Angel problem, the Cops and Robbers, the Surveillance game, the Eternal Dominating Set and Eternal Set Cover. One of the main ..."
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During the last decades, many combinatorial games involving two persons playing on a (directed) graph have received a lot of attention. Some examples of such games are the Angel problem, the Cops and Robbers, the Surveillance game, the Eternal Dominating Set and Eternal Set Cover. One of the main
Character Animation in Two-Player . . .
, 2010
"... The incorporation of randomness is critical for the believability and effectiveness of controllers for characters in competitive games. We present a fully automatic method for generating intelligent real-time controllers for characters in such a game. Our approach uses game theory to deal with the r ..."
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The incorporation of randomness is critical for the believability and effectiveness of controllers for characters in competitive games. We present a fully automatic method for generating intelligent real-time controllers for characters in such a game. Our approach uses game theory to deal
Predicting How People Play Games: Reinforcement Learning . . .
- AMERICAN ECONOMIC REVIEW
, 1998
"... ..."
Markov games as a framework for multi-agent reinforcement learning
- IN PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING
, 1994
"... In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed in their behavior ..."
Abstract
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Cited by 607 (13 self)
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-learning-like algorithm for finding optimal policies and demonstrates its application to a simple two-player game in which the optimal policy is probabilistic.
Designing Games With A Purpose
, 2008
"... Data generated as a side effect of game play also solves computational problems and trains AI algorithms. ..."
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Cited by 524 (2 self)
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Data generated as a side effect of game play also solves computational problems and trains AI algorithms.
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