Implementation of RL Algorithms
Picture from Reinforcement Learning - An Introduction
Abstract
To broaden my perspective on Machine Learning, I took up Reinforcement Learning courses by David Silver, Stanford CS234. To understand the nuances in the field, I implemented basic algorithms. The inspiration for the same was also drawn through a project where the idea of using Imitation Learning to overcome several limitations, struck me.
Implementated:
- DQN
- Vanilla Policy Gradient
- PPO
- DDPG
Results
Value and Policy Iteration
| Method | Deterministic Frozen Lake | Stochastic Frozen Lake |
|---|---|---|
| Value Iteration | 7 | 8 |
| Policy Iteration | 7 | 3 |
Q-Learning
Deep Q-Learning
