This paper provides a comprehensive overview of the applications of game theory in deep learning. Today, deep learning is a fast-evolving area for research in the domain of artificial intelligence. Alternatively, game theory has been showing its multi-dimensional applications in the last few decades...
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使学习者收益最小化的行动。这意味着单a...
(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...
Applications of game theory in deep learning: a surveyTanmoy Hazra 1 & Kushal Anjaria 2Received: 9 June 2021 /Revised: 29 August 2021 /Accepted: 3 January 2022# The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022AbstractThis paper...
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…
This paper provides a comprehensive overview of the applications of game theory in deep learning. Today, deep learning is a fast-evolving area for research in the domain of artificial intelligence. Alternatively, game theory has been showing its multi-dimensional applications in the last few decades...
dockermachine-learningreinforcement-learningjupyternotebookdecision-makingdeep-reinforcement-learningartificial-intelligencetensorboardgame-theorylesson UpdatedNov 18, 2020 Jupyter Notebook Collection of articles, books, videos and other things I found useful for those interested in the topic. ...
Osborne MJ (2004) An introduction to game theory, vol 3. Oxford University Press, New York Google Scholar Pan Z, Yu W, Yi X, Khan A, Yuan F, Zheng Y (2019) Recent progress on generative adversarial networks (GANs): a survey. IEEE Access 7:36322–36333 Article Google Scholar Pan ...
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
Game theory and multi-agent reinforcement learning. In M. Wiering and M. van Otterlo (Eds.), Reinforcement Learning. State-of-the-Art, pp. 441-470. Berlin and Heidelberg: Springer.Now´e, A., Vrancx, P., De Hauwere, Y.-M.: Game theory and multi-agent reinforce- ment learning....