Evolution strategy for policy search in robotics

Abstract

At the introduced article, we provide an enhancement to evolution strategy to generate more robust sub-optimal policies in reinforcement learning tasks. Our solution is applicable to the autonomous vehicles researches, where is a need of designing or detecting complex patterns in visual features and control policies, that cannot be described by human researcher.