1.1 multi-agent RL 问题建模 1.2 multi-agent RL 求解范式 二、协作型的 multi-agent 系统 2.1 协作机制 2.2 对话系统 2.3 控制系统 三、竞争型的 multi-agent 系统 3.1 竞争型的解释及其与协作型的比较 3.2 典型的竞争型的案例 参考资料 在上一篇关于 RAG 的讨论中已经延伸出了 multi-agent 系统的概念,那...
1.1、Multi Agent RL Wiki:en.wikipedia.org/wiki/M 多智能体强化学习是我认为与该思路最接近的一个方向,我认为实际上这个思路就是从该领域平移而来。 强化学习(RL)本来就已经是一个比较玄学的领域了,Multi Agent RL是RL中也比较玄学的领域,堪称“玄学的平方”。说实话我并不建议大家去深入钻这个领域,适当涉猎...
现在Multi-agent RL基本上相当于五年前的DRL，各种自制环境满天飞，评价准则也各有不同。调参较单智能体...
Multi-Agent RL指环境中的Agent多余一个，考虑的问题从single扩充到Multi的角度，问题的维度和角度相较...
Multi-Agent RL指环境中的Agent多余一个，考虑的问题从single扩充到Multi的角度，问题的维度和角度相较...
Multi-agent RL MADDPG Social Influence as Intrinsic Motivation AlphaStar 小细节 Model-based RL 从经验中学习一个 Model ,然后从 Model 上仿真学习。 AlphaGo to AlphaZero, MuZero AlphaGo -> AlphaGo Zero -> AlphaZero -> MuZero AlphaGo 可以理解为“很厉害的树搜索”,但是需要 pre-training 。
Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural networks further enhance its learning power. However, centralized RL is infeasible for large-scale ATSC due to the extremely high dimension of...
KiloBot-MultiAgent-RL This is an experimentation to learn about Swarm Robotics with help of MultiAgent Reinforcement learning. We have used KiloBot as a platform as these are very simple in the actions space and have very high degree of symmetry. The Main inspiration of this project is this ...
The dynamics between agents and the environment are an important component of multi-agent Reinforcement Learning (RL), and learning them provides a basis for decision making. However, a major challenge in optimizing a learned dynamics model is the accumulation of error when predicting multiple steps...
In this study, we propose a dynamic task assignment method for vehicles in urban transportation system based on the multi-agent reinforcement learning (RL). The transportation task assignment problem is transformed into a stochastic game process from vehicles' perspective, and then an extended actor-...