Reinforcement learning implementations and experiments

This repository contains implementations of reinforcement learning algorithms and experiments with environments using the OpenAI Gym API.

Algorithms

Dynamic programming

• Policy evaluation
• Policy iteration
• Value iteration

Monte Carlo

• Monte Carlo on-policy evaluation
• Monte Carlo on-policy control
• Monte Carlo off-policy evaluation
• Monte Carlo off-policy control

Temporal-difference

• TD(0)
• n-step TD
• SARSA
• Expected SARSA
• Q-Learning
• Double Q-Learning
• DQN

Gradient-methods

• Semi-gradient TD(0)
• Gradient Monte Carlo
• Semi-gradient Q-Learning
• Semi-gradient SARSA

Environments

• 2d grid world: A 2d rectangular grid world where agent can move deterministically up, down, left, right.
• 1d random walk: A 1d random walk reward-only process.

Experiments

• N-armed Bandit
• Gridworld
• Frozen Lake
• Taxi
• Randomwalk
• Mountaincar
• Cartpole