Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python
Tired of working with standard OpenAI Environments?
Want to get started building your own custom Reinforcement Learning Environments?
Need a specific Python RL environment built for a project you’re working on in the field?
In this video you’ll learn how to do exactly that in 25 minutes. In this video you’ll learn how to build a basic custom reinforcement learning environment to get started with reinforcement learning. We’ll go through how to build your own environment class, setting up the __init__, step and reset methods and then train a simple RL model to learn how to interact with it using Python, Keras-RL and OpenAI Gym.
In this video you'll go through:
1. How to build a custom environment with OpenAI Gym
2. Training a DQN Agent on a Custom OpenAI Environment
3. Testing out a Reinforcement Learning agent on a Custom Environment
Get the CODE: https://github.com/nicknochnack/OpenAI-Reinforcement-Learning-with-Custom-Environment
Chapters
0:00 - Start
0:30 - Cloning Baseline Reinforcement Learning Code
3:12 - Custom Environment Blueprint and Scenario
5:22 - Installing and Importing Dependencies
7:44 - Creating a Custom Environment with OpenAI Gym
9:21 - Coding the __init__() method for a OpenAI Environment
12:26 - Coding the step() method for an OpenAI Environment
16:50 - Coding the reset() method for an OpenAI Environment
17:23 - Testing a Custom OpenAI Environment
20:29 - Training a DQN Agent with Keras-RL
23:48 - Running a DQN Agent on a Custom Environment using Keras-RL
Oh, and don't forget to connect with me!
LinkedIn: https://www.linkedin.com/in/nicholasrenotte
Facebook: https://www.facebook.com/nickrenotte/
GitHub: https://github.com/nicknochnack
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!Tired of working with standard OpenAI Environments?
Tired of working with standard OpenAI Environments?
Want to get started building your own custom Reinforcement Learning Environments?
Need a specific Python RL environment built for a project you’re working on in the field?
In this video you’ll learn how to do exactly that in 25 minutes. In this video you’ll learn how to build a basic custom reinforcement learning environment to get started with reinforcement learning. We’ll go through how to build your own environment class, setting up the __init__, step and reset methods and then train a simple RL model to learn how to interact with it using Python, Keras-RL and OpenAI Gym.
In this video you’ll go through:
1. How to build a custom environment with OpenAI Gym
2. Training a DQN Agent on a Custom OpenAI Environment
3. Testing out a Reinforcement Learning agent on a Custom Environment
Get the CODE: https://github.com/nicknochnack/OpenAI-Reinforcement-Learning-with-Custom-Environment
Chapters
0:00 – Start
0:30 – Cloning Baseline Reinforcement Learning Code
3:12 – Custom Environment Blueprint and Scenario
5:22 – Installing and Importing Dependencies
7:44 – Creating a Custom Environment with OpenAI Gym
9:21 – Coding the __init__() method for a OpenAI Environment
12:26 – Coding the step() method for an OpenAI Environment
16:50 – Coding the reset() method for an OpenAI Environment
17:23 – Testing a Custom OpenAI Environment
20:29 – Training a DQN Agent with Keras-RL
23:48 – Running a DQN Agent on a Custom Environment using Keras-RL
Oh, and don’t forget to connect with me!
LinkedIn: https://www.linkedin.com/in/nicholasrenotte
Facebook: https://www.facebook.com/nickrenotte/
GitHub: https://github.com/nicknochnack
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!Tired of working with standard OpenAI Environments?
