SkyAI: Highly modularized reinforcement learning library

摘要

This paper introduces a software library of reinforcement learning (RL) methods, named SkyAI. SkyAI is a highly modularized RL library for real/simulated robots to learn behaviors. Our ultimate goal is to develop an artificial intelligence (AI) program with which the robots can learn to behave as their users' wish. In this paper, we describe the concepts, the requirements, and the current implementation of SkyAI. SkyAI provides two conflicting features: high execution-speed enough for real robot systems and high flexibility to design learning systems. We also demonstrate the applications to crawling tasks of both a humanoid robot in simulation and a real spider robot.