在单智体强化学习(single-RL)中,置信域方法(trust-region method)有两个比较典型的算法,分别是置信域策略优化算法Trust Region Policy Optimization (TRPO)以及近端策略优化算法Proximal Policy Optimization (PPO),他们在离散和连续RL问题上都表现出十分优越的性能。置信域方法的有效性,很大程度上源于其具有理论保证的...
To tackle this problem, we conduct a game-theoretical analysis in the policy space, and propose a multi-agent trust region learning method (MATRL), which enables trust region optimization for multi-agent learning. Specifically, MATRL finds a stable improvement direction that is guided by the ...
这使得问题不仅是一个单纯的强化学习问题,还伴随着对安全性的严格要求。 2.Multi-Agent Constrained Policy Optimization (MACPO) MACPO算法是基于信任域优化(Trust Region Optimization)的一种安全强化学习方法,核心思想是通过策略的逐步更新在保证安全的前提下实现奖励的单调提升。该方法的主要特点包括: 信任域约束:在...
Yang, “Trust region policy optimisation in multi-agent reinforcement learning,” in Proc. 10th Int. Conf. Learning Representations, 2022.. Google Scholar [21] T. Huynh-The, Q.-V. Pham, X.-Q. Pham, T. Nguyen, Z. Han, and D.-S. Kim. Artificial intelligence for the metaverse: A...
T. Kurutach, I. Clavera, Y. Duan, A. Tamar, and P. Abbeel, “Model-ensemble trust-region policy optimization,” arXiv preprint arXiv: 1802.10592, 2018.. Google Scholar [49] G. Hinton, O. Vinyals, and J. Dean, “Distilling the knowledge in a neural network,” arXiv preprint arXiv...
Collaborative optimization of multi-energy multi-microgrid system: A hierarchical trust-region multi-agent reinforcement learning approach This paper introduces a hierarchical Multi-agent Deep Reinforcement Learning (HMADRL) approach for distributed IEMS in MEMMG. Firstly, by employing a ... X Xu,K ...
Trust region policy optimisation in multi-agent reinforcement learning by Kuba, Jakub Grudzien, Ruiqing Chen, Munning Wen, Ying Wen, Fanglei Sun, Jun Wang, and Yaodong Yang, ICLR 2022. The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games by Chao Yu, Akash Velu, Eugene Vinit...
where rRM is the fraction of the RM with importance weights outside the trust region [1/C, C] and D is a parameter. The most notable hyperparameters used in our description of the MARL setup are the spatial resolution for the interpolation of the actions onto the grid (determined by ...
An efficient lossless ROI image compression using wavelet-based modified region growing algorithm P Sreenivasulu, S Varadarajan – Journal of Intelligent Systems, 2020 – degruyter.com De Gruyter De Gruyter …Gbest-Guided Artificial Bee Colony Optimization Algorithm-Based Optimal Incorporation of Shunt ...
Multi-agent Proximal Policy Optimization (MAPPO)[42]: This is a multi-agent version of Proximal Policy Optimization (PPO) [43], which improves the trust region policy optimization (TRPO) [44] by using a clipped surrogate objective and adaptive KL penalty coefficient. ...