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Solution to Cartpole balancing problem with the help of reinforcement learning and Deep Neural Networks.

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CartPole-v0

#Solution to Cartpole balancing problem with the help of reinforcement learning and Deep Neural Networks.

I highly recommend going through following blogs and videos if you are new to RL

  1. Thomos Simonini: Reinforcement Learning with Q Learning: https://lnkd.in/eh46x3V
  2. Cartpole balancing with q learning: https://medium.com/@tuzzer/cart-pole-balancing-with-q-learning-b54c6068d947
  3. An overview of reinforcement learning teaching machines to play games: https://pythonmachinelearning.pro/an-overview-of-reinforcement-learning-teaching-machines-to-play-games/
  4. OpenAI cartpole using Neural Networks by Sentdex : https://pythonprogramming.net/openai-cartpole-neural-network-example-machine-learning-tutorial/
  5. Reinforcement Learning by Jacob Schrum : https://lnkd.in/eRS2vBY
  6. Reinforcement Learning by David Silver : https://lnkd.in/ebtdXkd

The code is well explaind by blog no 2 and 3 and it works very well using Q learning algorithm by stabilizing the pole for 200 timsteps I have also tried to solve the problem using Sarsa, it is also working fine but we only have to set the discount rate = 0.98.

A Deep Neural Network can also come up with the solution to this problem, go through Sentdex's website (no. 4) for more info.

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