Adaptive Critic Design with Echo State Network

摘要

In the present paper an application of a novel neural network architecture called Echo State Network (ESN) within the frame of a reinforcement learning scheme named Adaptive Critic Design (ACD) is proposed. Our aim is to investigate the possibility for on-line training of adaptive critic using the ESN architecture. In particular the application of this approach to mobile robot control is presented. Our preliminary results are encouraging and demonstrate that ESNs are good candidates for the on-line application of an ACD optimization approach due to their specific structure and fast training algorithm.