Investigating Reinforcement Learning Agents for Continuous State Space Environments

08/08/2017

∙

by   David Von Dollen, et al.

∙

0

∙

share

Given an environment with continuous state spaces and discrete actions, we investigate using a Double Deep Q-learning Reinforcement Agent to find optimal policies using the LunarLander-v2 OpenAI gym environment.