Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms Native8418 会的不多,每天学一点是一点 创作声明:包含 AI 辅助创作 2 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)取得了显著的进步,并在解决机器学习中的各种序贯决策问题上取得了...
De Schutter, Multi-agent reinforcement learning: An overview. In Innovations in Multi-Agent Systems and Applications, pp. 183-221, 2010, Springer Berlin Heidelberg.L. Buşoniu, R. Babuška, B. De Schutter, Multi-agent reinforcement learning: An overview, in: Innovations in Multi-Agent ...
^Tan, M. (1993). Multi-agent reinforcement learning: Independent vs. cooperative agents. In Proceedings of the tenth international conference on machine learning, pages 330– 337. ^Lauer, M. and Riedmiller, M. (2000). An algorithm for distributed reinforcement learning in cooperative multi-agen...
Recent years have witnessed significant advances in reinforcement learning (RL), which has registered tremendous success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving...
Multi-agent Reinforcement Learning: An Overview BT - Innovations in Multi-Agent Systems and Applications - 1 L Buşoniu,R Babuška,B De Schutter 被引量: 0发表: 2010年 Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm In this paper, we adopt general-sum stochastic games...
Recent years have witnessed significant advances in reinforcement learning (RL), which has registered great success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving, ...
However, simulations of turbulent flows remain hindered by the inability of heuristics and supervised learning to model the near-wall dynamics. We address this challenge by introducing scientific multi-agent reinforcement learning (SciMARL) for the discovery of wall models for large-eddy simulations (...
Multi-agent reinforcement learning and its application to role assignment of robot soccer多智能体强化学习及其在足球机器人角色分配中的应用 Robot soccer is a typical multi-agent system. The action selected by each robot player not only depends on the current field state, but is also impacted by.....
“Multi-Agent Reinforcement Learning for Urban Crowd Sensing with For-Hire Vehicles”论文笔记 论文介绍: 背景:近年来,利用配备传感器的城市车辆收集城市尺度的感知数据的车辆人群感知(VCS)已成为一种有前景的城市感知范式。如今,由于私家车难以满足的各种硬件和软件限制,很多VCS任务都是由租赁车辆(FHVs)完成的。
综述阅读: 《Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms》 storm 22 Fall PhD Student @ LLM3 人赞同了该文章 一篇MARL的近期高引综述(2020年)发布于 2021-11-03 17:31 内容所属专栏 强化学习入门 记录小白入门历程(长期更新) 订阅专栏 ...