Reinforcement Learning Algorithms with Python

Appling DDPG to BipedalWalker-v2

Let's now apply DDPG to a continuous task called BipedalWalker-v2, that is, one of the environments provided by Gym that uses Box2D, a 2D physical engine. A screenshot of this environment follows. The goal is to make the agent walk as fast as possible in rough terrains. A score of 300+ is given for moving until the end, but every application of the motors costs a small amount. The more optimally the agent moves, the less it costs. Furthermore, if the agent falls, it receives a reward of -100. The state consists of 24 float numbers that represent the speeds and the positions of the joints and the hull, and LiDar rangefinder measurements. The agent is controlled by four continuous actions, with the range [-1,1]. ...