This repository contains exercises and projects I've worked on for the nanodegree.
These are my reports for the three main projects, trained using Unity ML-Agents.
| Navigation | Continuous Control | Collaboration and Competition |
|---|---|---|
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| Implemented with a Dueling DDQN. See the README and the report. | Implemented with A2C-GAE. See the README and the report. | Implemented with MADDPG and self-play. See the README and the report. |
Also, here's a list of exercise notebooks trained on a few OpenAI Gym environments.
- Monte Carlo methods
- Temporal difference methods (SARSA, Q-Learning, Expected-Sarsa)
- Discretization and tile coding (Q-Learning)
- Deep Q-Network
- Policy based methods (Hill Climbing, Cross Entropy Method)
- Policy gradient methods (REINFORCE, PPO)
Some python scripts derived from the notebooks are provided as well.