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

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Name		Name	Last commit message	Last commit date
Latest commit History 77 Commits
.ipynb_checkpoints		.ipynb_checkpoints
DDPG		DDPG
DQN		DQN
Dynamic Programming		Dynamic Programming
Monte Carlo		Monte Carlo
Policy Gradients		Policy Gradients
LICENSE		LICENSE
README.md		README.md

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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

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

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