计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2014年
12期
4320-4323,4328
,共5页
交互%博弈学习%多智能体%均衡%学习因子
交互%博弈學習%多智能體%均衡%學習因子
교호%박혁학습%다지능체%균형%학습인자
interaction%game learning%multi-Agent%equilibrium%learning factor
由于人们之间的博弈行为受多种因素的制约和影响，而传统的博弈方法很难处理这种影响因素多变、交互关系复杂的博弈问题，给出一个基于博弈学习的多智能体（multi‐Agent）交互模型，并以此为基础构建多Agent交互的博弈学习方法。对合作小组中成员的行为进行修正，通过博弈学习中学习因子的更新得到局部均衡，达到全局利益优化。实例仿真验证了该方法的可行性。
由于人們之間的博弈行為受多種因素的製約和影響，而傳統的博弈方法很難處理這種影響因素多變、交互關繫複雜的博弈問題，給齣一箇基于博弈學習的多智能體（multi‐Agent）交互模型，併以此為基礎構建多Agent交互的博弈學習方法。對閤作小組中成員的行為進行脩正，通過博弈學習中學習因子的更新得到跼部均衡，達到全跼利益優化。實例倣真驗證瞭該方法的可行性。
유우인문지간적박혁행위수다충인소적제약화영향，이전통적박혁방법흔난처리저충영향인소다변、교호관계복잡적박혁문제，급출일개기우박혁학습적다지능체（multi‐Agent）교호모형，병이차위기출구건다Agent교호적박혁학습방법。대합작소조중성원적행위진행수정，통과박혁학습중학습인자적경신득도국부균형，체도전국이익우화。실례방진험증료해방법적가행성。
Taking the increasingly complex sociability into consideration ,people’s behavior is restricted and influenced by many factors .However ,it is very difficult for the traditional game method to deal with the game problems with polytrophic influence factors and complex interactive relations .A multi‐Agent interaction model based on game theory learning was given to solve this problem .On this basis of the model ,a multi‐Agent’s interactive game learning methods was constructed ,which was used to correct the behaviors of team members ,and partial equilibrium was achieved by updating the learning factors of game learning , so that the global optimization was ultimately achieved .The simulation results show that the method is feasible .
