Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps

This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates two features that significantly enhance a robot’s action selection capability: self-organization in the continuous state and action spaces to provide smooth, efficient and fine motion control; action selection via the cooperation and competition of Extended Kohonen Maps to achieve more complex motion tasks. Qualitative and quantitative comparisons for single- and multirobot tasks show our framework can provide better action selection than do potential fields method.

• Type: Conference
• Year: 2003
• Where: IJCAI
• Authors: Kian Hsiang Low, Wee Kheng Leow, Marcelo H. Ang Jr.
• Keywords: Action Selection, Action Selection Framework, Extended Kohonen Maps, IJCAI 2003, IJCAI 2007