Generating Cooperative Behavior by Multi-Agent Profit Sharing on the Soccer Game
Generating Cooperative Behavior by Multi-Agent Profit Sharing on the Soccer Game
复制标题
足球比赛中多智能体利润分享生成合作行为
DOI：
10.1007/11554028_102
复制
发表时间：
2003
影响因子：
4.6
通讯作者：
Hiroaki Kobayashi
中科院分区：
文献类型：
--
作者：
K. Miyazaki;T. Terada;Hiroaki Kobayashi
提出了一种基于贝叶斯网络（BNs）混合模型的强化学习（RL）智能体在线策略改进系统，并讨论了该系统的性质。本文将两种混合模型应用于该系统。混合模型中BN的结构是基于agent在一个环境中收集的数据来选择的，它被看作是对环境的随机知识。本研究探讨了我们的系统对动态环境的适应性，包括一个没有经验的环境，在这个环境中，agent没有知识。
We have proposed an online policy-improving system of reinforcement learning (RL) agents with a mixture model of Bayesian Networks (BNs), and discussed properties of the system. In this paper, two types of mixture models have been applied to the system. A structure of BN in the mixture model is selected based on data collected by agents in an environment, and is regarded as a stochastic knowledge of the environment. This research investigates the adaptability of our system to dynamic environments containing an unexperienced environment, in which an agent does not have the knowledge.