The following labs are intended to give a basic introduction to the Ray distributed programming framework and examples of its use for 3 AI algorithms. This includes distributed implementations of Value Iteration for Markov Decision Process Planning, table-based Reinforcement Learning, and DQN for Deep Reinforcement Learning.

Direct any feedback to Alan Fern.

This lab introduces the basic Ray framework for distributed programming.

This lab develops a distributed implementation of the Value Iteration algorithm for MDP planning.

This lab develops and compares distributed implementations of the table-based reinforcement learning algorithms: Q-learning and SARSA.

This lab develops a distributed implementation of the DQN
algorithm for deep reinforcement learning.

· lab4.zip