Hands-On Reinforcement Learning with Python

Training a robot to walk

Now let's learn how to train a robot to walk using Gym along with some fundamentals.

The strategy is that X points will be given as a reward when the robot moves forward, and if the robot fails to move then Y points will be reduced. So the robot will learn to walk in the event of maximizing the reward.

First, we will import the library, then we will create a simulation instance by the make function. Open AI Gym provides an environment called BipedalWalker-v2 for training robotic agents in a simple terrain:

import gymenv = gym.make('BipedalWalker-v2')

Then, for each episode (agent-environment interaction between the initial and final state), we will initialize the environment using the reset method:

for episode