这意味着单agent Q-learning的max算子被minimax值代替: (3)假设行动者将采取均衡策略 例如:Nash-Q (Hu and Wellman, 2003)观察了所有智能体的回报,并保持了q值的估计,不仅是学习智能体,而且是所有其他智能体。这允许学习者将每个状态下的联合行动选择表示为一个博弈,其中支付矩阵中的条目由联合行动的agent的q值定...
(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...
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…
Specifically, we propose a novel game model which incorporates the vital element of online information and provide a discussion of possible solutions as well as promising future research directions based on game theory and deep reinforcement learning.Lantao Yu...
This paper is to discuss the development of Deep Reinforcement Learning and the future of it from the perspective of Game Theory. The relationship and potential interaction between these two areas are also introduced, especially the optimization method. This paper discusses about the situations both ...
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...
approach can be seen as a Stackelberggame. Generative Adversarial Network (GAN) is a deep learning architecture that hasgained popularity in solving complex computer vision problems. GANs have their rootsin game theory. The training of the generators and discriminators in GANs is essentially atwo-...
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...
Future work and research directions Although game theory has been applied to real problems in different domains such as political science, biology, and engineering, the assumption that players are rational and have common knowledge so they aim at maximizing profit and minimizing cost is not always ...
The work in [161] proposed deep reinforcement learning-based game for solving computation offloading problem. Another work [162] combined mean-field game theory with deep reinforcement learning for solving the task allocation problem. Game theory has also been integrated with Generalized Adversarial ...