Add to ORKG对目前世界上分布式强化学习方法的研究成果加以总结,分析比较了独立强化学习、社会强化学习和群体强化学习三类分布式强化学习方法的特点、差别和适用范围,并对分布式强化学习仍需解决的问题和未来的发展方向进行了探讨
With great success in Reinforcement Learning’s application to a suite of single-agent environments, ...
10.1109/ICTAI.2011.75Proceedings - International Conference on Tools with Artificial Intelligence, I...
Reinforcement learning has been widely applied to solve a diverse set of learning tasks, from board ...
对目前世界上分布式强化学习方法的研究成果加以总结,分析比较了独立强化学习、社会强化学习和群体强化学习三类分布式强化学习方法的特点、差别和适用范围,并对分布式强化学习仍需解决的问题和未来的发展方向进行了...
在多机器人系统中 ,评价一个机器人行为的好坏常常依赖于其它机器人的行为 ,此时必须采用组合动作以实现多机器人的协作 ,但采用组合动作的强化学习算法由于学习空间异常庞大而收敛得极慢 .本文提出的新方法通...
在人工智能领域中 ,强化学习理论由于其自学习性和自适应性的优点而得到了广泛关注 随着分布式人工智能中多智能体理论的不断发展 ,分布式强化学习算法逐渐成为研究的重点 首先介绍了强化学习的研究状况 ,然后...
Abstract Multi-agent systems are rapidly nding applications in a variety of domains, including robo...
Artificial intelligence algorithms enable autonomous agents to perform sophisticated tasks with grea...
Reinforcement learning techniques have been successfully used to solve single agent optimization pro...
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, dis...
This paper describes a multi-agent influence learning approach and reinforcement learning adaptatio...
Proceeding of: 6th Ibero-American Conference on AI (IBERAMIA '98),Lisbon, Portugal, October 5–9, 199...
Achieving distributed reinforcement learning (RL) for large-scale cooperative multi-agent systems (M...
Multi-agent reinforcement learning for incomplete information environments has attracted extensive a...
We apply diffusion strategies to develop a fully-distributed cooperative reinforcement learning algo...
With great success in Reinforcement Learning’s application to a suite of single-agent environments, ...
10.1109/ICTAI.2011.75Proceedings - International Conference on Tools with Artificial Intelligence, I...
Reinforcement learning has been widely applied to solve a diverse set of learning tasks, from board ...
对目前世界上分布式强化学习方法的研究成果加以总结,分析比较了独立强化学习、社会强化学习和群体强化学习三类分布式强化学习方法的特点、差别和适用范围,并对分布式强化学习仍需解决的问题和未来的发展方向进行了...
在多机器人系统中 ,评价一个机器人行为的好坏常常依赖于其它机器人的行为 ,此时必须采用组合动作以实现多机器人的协作 ,但采用组合动作的强化学习算法由于学习空间异常庞大而收敛得极慢 .本文提出的新方法通...
在人工智能领域中 ,强化学习理论由于其自学习性和自适应性的优点而得到了广泛关注 随着分布式人工智能中多智能体理论的不断发展 ,分布式强化学习算法逐渐成为研究的重点 首先介绍了强化学习的研究状况 ,然后...
Abstract Multi-agent systems are rapidly nding applications in a variety of domains, including robo...
Artificial intelligence algorithms enable autonomous agents to perform sophisticated tasks with grea...
Reinforcement learning techniques have been successfully used to solve single agent optimization pro...
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, dis...
This paper describes a multi-agent influence learning approach and reinforcement learning adaptatio...
Proceeding of: 6th Ibero-American Conference on AI (IBERAMIA '98),Lisbon, Portugal, October 5–9, 199...
Achieving distributed reinforcement learning (RL) for large-scale cooperative multi-agent systems (M...
Multi-agent reinforcement learning for incomplete information environments has attracted extensive a...
We apply diffusion strategies to develop a fully-distributed cooperative reinforcement learning algo...
With great success in Reinforcement Learning’s application to a suite of single-agent environments, ...
10.1109/ICTAI.2011.75Proceedings - International Conference on Tools with Artificial Intelligence, I...
Reinforcement learning has been widely applied to solve a diverse set of learning tasks, from board ...