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Solving the cartpole problem using reinforment learning techniques such as Q-Learning and DQN.

Python 100.00%

reinforcement-learning q-learning deep-q-learning cartpole-v0 python artificial-intelligence neural

cartpole-v0's Introduction

Cartpole-V0

We took up the Cartpole-v0 problem in the OpenAI gym toolkit in order to carry out this project. This problem is said to be solved when the average reward over 100 consecutive episodes is equal to or greater than 195.
Through the use of reinforcement learning techniques, we successfully constructed a Q-learning agent and a Deep Q-learning Network agent which successfully solved the problem.
Additionally, the DQN agent arrived at an optimal policy which successfully attained an average reward of a perfect 200 after completion of neural network training.

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