计算机工程与应用Issue(8)：257-260,4.DOI:10.3778/j.issn.1002-8331.1108-0514
动作预测在多机器人强化学习协作中的应用
曹洁 1朱宁宁1
作者信息
- 1. 兰州理工大学 计算机与通信学院，兰州 730050
- 折叠
摘要
Abstract
In multi-robot systems, the spatial scale of reinforcement learning of the cooperation environment exploration is made up of the exponential function of the number of robots. And the enormous learning space results in the slow convergence rate. To solve this problem, a prediction-based reinforcement learning algorithm and the action selection strategy are applied to the research on multi-robot cooperation. By predicting the probability of actions that other robots may execute, the convergence rate of this algorithm is accelerated. The experimental results show that reinforcement learning algorithm based-on action predic-tion can achieve the multi-robot’s cooperation strategy much faster, compared to the primitive algorithm.关键词
动作预测/强化学习/多机器人协作Key words
action prediction/reinforcement learning/multi-robot cooperation分类
信息技术与安全科学引用本文复制引用
曹洁,朱宁宁..动作预测在多机器人强化学习协作中的应用[J].计算机工程与应用,2013,(8):257-260,4.
