深度强化学习(DRL)在各种挑战性问题中发挥了重要作用,并取得了显著成功,如回合制游戏[1]、[2]、实时视频游戏[3]、[4]、机器人控制[5]、自动优化[6]、[7]和图像分类[8]。作为一种扩展,多智能体强化学习(MARL)在许多场景中也受到了越来越多的关注,其中独立的智能体由于缺乏合作而无法完成复杂的任务[9]。MA...
Learning team-based navigation: a review of deep reinforcement learning techniques for multi-agent pathfindingdoi:10.1007/s10462-023-10670-6Multi-agent pathfinding (MAPF) is a critical field in many large-scale robotic applications, often being the fundamental step in multi-...
In their experiments, the agents should learn a discrete set of vocabulary by solving navigation tasks through communication. By involving more than three agents in the conversation and by penalizing an arbitrary size of vocabulary, agents agreed on a coherent set of vocabulary and discouraged ...
The Strategy Entropy of Reinforcement Learning for Mobile Robot Navigation in Complex Environments In this paper, the concept of entropy is introduced into reinforcement learning for mobile robot control. The definitions of the local and global strategy ... X Zhuang - IEEE 被引量: 5发表: 2005年...
Additional navigation options master BranchesTags Code Folders and files Name Last commit message Last commit date Latest commit History 480 Commits heuristics lessons madrl_environments maps pipelines rllab @ c9cc397 rllabwrapper rltools @ c2fbcd3 ...
In the field of multi-agent deep reinforcement learning (MADRL), agents can improve the overall learning performance and achieve their objectives by communication. Agents can communicate various types of messages, either to all agents or to specific agent groups, or conditioned on specific ...
Additional navigation options main 1Branch0Tags Code This branch is up to date withpengguo318/MaDRLAM:main. Folders and files Name Last commit message Last commit date Latest commit pengguo318 Add files via upload Nov 21, 2022 58139a9·Nov 21, 2022 ...
Then, agents analyze the navigation situation and make motion decisions accordingly. In particular, specific reward function schemas are designed to simulate the degree of cooperation among agents. According to the International Regulations for Preventing Collisions at Sea (COLREGs), three typical ...
# Example:agents=[]config=Config(env.dim,env.out,madrl=FLAGS.madrl,gpu=FLAGS.processor)# Agents are instantiatedforiinrange(FLAGS.agents):agent_config=deepcopy(config)agents.append(Agent(agent_config))# Init agent instances# !--- Store agent instances in agents list ---!
The smart grid utilizes the demand side management technology to motivate energy users towards cutting demand during peak power consumption periods, which greatly improves the operation efficiency of the power grid. However, as the number of energy users participating in the smart grid continues to in...