Decision-making and simulation in multi-agent robot system based on PSO-neural network

被引：0

作者：

Peng, Liang ^{[1
]}

Liu, Hai Yun ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Econ, Wuhan 430074, Peoples R China

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-5 | 2007年

关键词：

decision-making; multi-agent robot system; neural network; PSO;

D O I：

10.1109/ROBIO.2007.4522432

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In multi-agent robot system, each robot must behave by itself according to its states and environments. This paper proposes a method using neural networks and particle swarm optimization (PSO) for the decision-making in the multi-agent robot system. In this paper, a neural network is used for behavior decision controller. The inputs of the neural network are decided by the last actions of other robots. Then the outputs determine the next action that the robot will choose. The weight values imply the adaptiveness of robots in multi-agent robot system. The validity of the decision model is verified through simulation experiments and we could have observed the robots' emergent behaviors during simulation.

引用

页码：1763 / 1768

页数：6