Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python

Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python

Nicholas Renotte via YouTube Direct link

- Training a DQN Agent with Keras-RL

10 of 11

10 of 11

- Training a DQN Agent with Keras-RL

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Classroom Contents

Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python

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  1. 1 - Start
  2. 2 - Cloning Baseline Reinforcement Learning Code
  3. 3 - Custom Environment Blueprint and Scenario
  4. 4 - Installing and Importing Dependencies
  5. 5 - Creating a Custom Environment with OpenAI Gym
  6. 6 - Coding the __init__ method for a OpenAI Environment
  7. 7 - Coding the step method for an OpenAI Environment
  8. 8 - Coding the reset method for an OpenAI Environment
  9. 9 - Testing a Custom OpenAI Environment
  10. 10 - Training a DQN Agent with Keras-RL
  11. 11 - Running a DQN Agent on a Custom Environment using Keras-RL

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