Fast Reinforcement Learning through Eugenic Neuro-Evolution
Daniel Polani, Risto P Miikkulainen · 1999
In this paper we introduce EuSANE, a novel reinforcement learning algorithm based on the SANE neuroevolution method. It uses a global search algorithm, the Eugenic Algorithm, to optimize the selection of neurons to the hidden layer of SANE networks. The performance of EuSANE is evaluated in the two-pole balancing benchmark task, showing that EuSANE is significantly stronger than other reinforcement learning methods to date in this task.