원문정보
초록
영어
Risk dominance and payoff dominance strategy are two complementary parts of the game theory decision strategy. While payoff dominance is still the basic principle in perfect information, two player games, risk dominance has shown its advantages in imperfect information conditions. In this paper, we first review the related work in the area of estimation methods and the influence of risk factors on computing game equilibrium. Then a new algorithm, UCT-Risk is proposed in this paper, which is a modification of UCT (UCB apply to Trees) algorithm based on risk estimation methods. Finally, we implement the proposed algorithm in SiGuo game, a popular imperfect information game in China. The experimental result of the new algorithm shows it correctness and effectiveness.
목차
1. Introduction
2. Monte Carlo Method and UCT
3. Estimating Risks in Imperfect Information Conditions
4. UCT-Risk Algorithm
5. Experiments and Performance Evaluation
5.1. Parameters Set in Experiments
5.2. Experiments against Other UCT Policies
6. Conclusions
Acknowledgements
References