action selection in continuous state and action spaces by cooperation and competition of 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 tests demonstrate the capability of our action selection method for both single- and multi-robot motion tasks.
action selection neural networks motion control