UCT-RAVE Algorithm Applied to Multi-player Games with Imperfect Information
Aiming at the problems that traditional gaining search algorithms do not suit to multi-player games with imperfect information, a method of combining UCT-RAVE(Upper Confidence bound applied to Tree - Rapid Action Value Estimation) and Monte-Carlo sampling is proposed after analyzing the principle and characteristic of UCT-RAVE algorithm. First, the imperfect information is replaced by simulated perfect information through Monte-Carlo sampling then UCT-RAVE is used for searching based on that perfect information, at last most suitable action is selected after considering the best profits of many MonteCarlo samples. Simulation demonstrated the feasibility and the effectiveness of the method.
multi-player games with imperfect information UCT-RAVE algorithm Monte-Carlo sampling gaming search card gaming
Rui Xiongli Rui Xiongxing He Yinglai
Col, Communication Engineering Nanjing Institute of Technology Nanjing, China Col, Electronic and Info Engineering, China Col, Law Nanjing University of Technology Nanjing, China
国际会议
重庆
英文
312-315
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）