A NEAT Way for Evolving Echo State Networks

  title={A NEAT Way for Evolving Echo State Networks},
  author={Kyriakos C. Chatzidimitriou and Pericles A. Mitkas},
The Reinforcement Learning (RL) paradigm is an appropriate formulation for agent, goal-directed, sequential decision making. In order though for RL methods to perform well in difficult, complex, real-world tasks, the choice and the architecture of an appropriate function approximator is of crucial importance. This work presents a method of automatically… CONTINUE READING