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Approximate Dynamic Programming / Reinforcement Learning 2015/16 @ TUM

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Action.pyc		Action.pyc
Actions.py		Actions.py
Actions.pyc		Actions.pyc
Agent.py		Agent.py
Agent.pyc		Agent.pyc
Main.py		Main.py
README.md		README.md
State.py		State.py
State.pyc		State.pyc

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ADPRL2015

Solving a simple maze navigation problem with dynamic programming techniques: policy iteration and value iteration.

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Approximate Dynamic Programming / Reinforcement Learning 2015/16 @ TUM

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