Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms Native8418 会的不多,每天学一点是一点 来自专栏 · 零碎知识点 创作声明:包含 AI 辅助创作 5 人赞同了该文章 目录 收起 摘要 介绍 总结 部分概念解释 摘要 近年来,强化学习(RL)取得了显著
In this category, we have four algorithms: Multi-Agent Deep Deterministic Policy Gradient (MADDPG): MADDPG [4] is the multi-agent version of the DDPG algorithm [3], where the critic is trained centralised to approximate the joint state-action value. Counterfactual Multi-Agent Policy Gradient (...
Multi-Agent Learning II: AlgorithmsMulti-agent learning (MAL) refers to settings in which multiple agents learn simultaneously. Usually defined in a game theoretic setting, specifically in repeated games or stochastic games, the key...doi:10.1007/978-0-387-30164-8_564Yoav Shoham...
specifically in repeated games or stochastic games, the key feature that distinguishes MAL from single-agent learning is that in the former the learning of one agent impacts the learning of others. As a result, neither the problem definition for ...
The multi-agent system uses reinforcement learning algorithms to perform unsupervised learning. An excellent review of reinforcement learning agents can be seen in [18], [22], [27]. We give a brief introduction to reinforcement learning in the next section. ...
reinforcement-learningdeep-learningreinforcement-learning-algorithmsimitation-learninginverse-reinforcement-learningpytorch-rlmodel-based-reinforcement-learningmulti-agent-reinforcement-learningoffline-rl UpdatedMar 10, 2025 Python Code for paper "基于多智能体深度强化学习的车联网通信资源分配优化" ...
% 本文参照文献:Flocking for Multi-Agent Dynamic Systems:Algorithms and Theory clear; close all; clc; %% Parameters 初始化参数 num_agents = 100; t_gap=1; % 迭代间隔 queue_gap=15; % 队形间隔 queue_vy=12; queue_vx=13; queue_r=40; ...
pythonreinforcement-learningimpalareinforcement-learning-algorithmsminigridatariimitation-learningdistributed-systemdrlinverse-reinforcement-learningr2d2smacmujocomultiagent-reinforcement-learningpytorch-rlself-playmodel-based-reinforcement-learningexploration-exploitationdistributed-reinforcement-learningoffline-rl ...
Learning and Adaptation (LEARN) Area Chairs: Long Tran-Thanh, Bo An, Marc Lanctot, Chongjie Zhang, Jianye Hao, Haifeng Xu Topics: Reasoning and learning under uncertainty Supervised learning Unsupervised and representation learning Reinforcement learning Multiagent learning Evolutionary algorithms Learning ...
To address this class of problems, we have proposed algorithms which are decentralized in the sense that they enable each agent to compute its own cell independently from its teammates without utilizing, for instance, a common spatial grid. The main caveat of the approach proposed in [12], [...