(d)性别博弈,各主体偏好不同的协调博弈)纯纳什均衡用粗体表示。 博弈a:玩家1和玩家2一起抛硬币,若是双方硬币是同一面的,则玩家1获胜,否则玩家2获胜。零和博弈 博弈b:囚徒博弈,一般和博弈。 博弈c:一个共同兴趣游戏。在这种情况下,两个玩家在每次联合行动中获得相同的收益。这个游戏的挑战是让玩家协调最优的...
代表在状态s下采取ak,而其他智能体采取 的Q值,这些期望的q值可以用于agent的动作选择,以及Q-learning的更新,就像在标准的单智能体的Q-learning算法中一样。 (2)假设其他智能体将根据某种策略进行博弈 例如:在minimax Q-learning算法(Littman, 1994)中,该算法是针对二主体零和问题而开发的,学习主体假设其对手将采取...
Game Theory and Multi-agent Reinforcement Learning笔记 上,一、引言多智能体强化学习的标准模型:多智能体产生动作a1,a2...an联合作用于环境,环境返回当前的状态st和奖励rt。智能体接受到系统的反馈st和ri,根据反馈信息选择下一步的策略。二、重复博弈正规形式
强化学习起初是因为马尔科夫决策过程发展起来的。它可以让单个智能体去学习一个策略,这个策略可以在随机且稳定的环境中最大化可能的延迟奖励信号。只要智能体能够充分的实验,并且智能体运行的环境是马尔科夫模型…
Reinforcement learning and game theory based cyber-physical security framework for the humans interacting over societal control systemsdoi:10.3389/fenrg.2024.1413576Cao, YajuanTao, ChenchenXia, YangTaher, FatmaFrontiers in Energy Research
另外帮忙PR一下腾讯的智能体中心（原强化学习中心），目前的一大方向就是Game-Theoretic RL，做一些博弈...
In this work, we focus on using reinforcement learning and game theory to solve for the optimal strategies for the dice game Pig, in a novel simultaneous playing setting. First, we derived analytically the optimal strategy for the 2-player simultaneous g
The algorithm is based on game theory and reinforcement learning approach. We compared the performance of our algorithm with that of online bin packing and MAB algorithm. We observed that our algorithm performs better than online bin packing when there is a variation in the deadlines. This is ...
摘要: We propose the use of game-theoretic solutions and multi- agent Reinforcement Learning in the mechanism design of smart, sustainable mobility services. In particular, we present applications to ridesharing as an example of a cost game....
game-theorygame-design UpdatedJul 29, 2020 An open-source Python library for poker game simulations, hand evaluations, and statistical analysis gamepythonreinforcement-learningpokerdeep-learninggame-developmentartificial-intelligencegame-theorypoker-enginepoker-gametexas-holdempoker-handspoker-evaluatorpoker-libra...