Running GAIL on PyBullet Gym

For our code example in this chapter, we will train a virtual agent to navigate a simulated environment – in many RL papers, this environment is simulated using the Mujoco framework (http://www.mujoco.org/). Mujoco stands for Multi joint dynamics with contacts – it is a physics "engine" that allows you to create an artificial agent (such as a pendulum or bipedal humanoid), where a "reward" might be an ability to move through the simulated environment.

While it is a popular framework used for developing reinforcement learning benchmarks, such as by the research group OpenAI (see https://github.com/openai/baselines for some of these implementations), it is also closed source and requires a license for use. For our experiments, we will use PyBullet Gymperium (https://github.com/benelot/pybullet-gym), a drop-in replacement for Mujoco that allows us to run a physics simulator and import agents trained in Mujoco...