akjayant / Coding_Reinforcement_Learning

Implementation of basic RL steps and algorithms - Dynamic Programming approach, Monte-Carlo approach, DQN on Atari, Policy Gradient - Reinforce with baseline, Actor Critic (A2C)

Geek Repo

Github PK Tool

reinforcement-learning grid-world policy-iteration policy-evaluation monte-carlo-simulation blackjack-game monte-carlo-methods rl-steps algorithms policy-gradient dqn atari pong

Coding the RL elements

Implementation of basic RL steps and algorithms with my personal snippets/notes in jupyter notebook.

References -

Intro to RL - Sutton & Barto
Denny Britz RL Repo - blackjack.py, gridworld.py, plotting.py

About

Implementation of basic RL steps and algorithms - Dynamic Programming approach, Monte-Carlo approach, DQN on Atari, Policy Gradient - Reinforce with baseline, Actor Critic (A2C)

reinforcement-learning grid-world policy-iteration policy-evaluation monte-carlo-simulation blackjack-game monte-carlo-methods rl-steps algorithms policy-gradient dqn atari pong

MIT License

Languages

Language:Jupyter Notebook 95.9%Language:Python 4.1%