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