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YouTube

Build a Doom AI Model with Python - Gaming Reinforcement Learning Full Course

Nicholas Renotte via YouTube

Overview

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Learn how to teach AI to play Doom by installing VizDoom for Python, preparing it for Reinforcement Learning with OpenAI Gym, building Reinforcement Learning AI models using Stable Baselines 3, training for different Doom levels, and applying Curriculum Learning and Reward Shaping to enhance results. The course covers setting up the environment, training the RL model, testing the agent, and analyzing AI results for various Doom levels. The intended audience for this course includes Python developers interested in gaming and AI, particularly in reinforcement learning applications.

Syllabus

- Start
- Introduction
- Explainer
- CLIENT CONVERSATION 1
- Animation 1
- Tutorial Kickoff
- Getting VizDoom up and running
- CLIENT CONVERSATION 2
- Animation 2
- Creating an OpenAI Gym Environment
- CLIENT CONVERSATION 3
- Animation 3
- Setup Training Callback
- Train the RL model
- CLIENT CONVERSATION 4
- Testing the Agent
- BASIC LEVEL AI RESULTS
- CLIENT CONVERSATION 5
- Animation 4
- Changing Levels
- DEFEND CENTER LEVEL AI RESULTS
- CLIENT CONVERSATION 6
- Reward shaping
- Curriculum Learning
- DEADLY CORRIDOR LEVEL AI RESULTS
- FINAL CLIENT CALL
- Wrap up

Taught by

Nicholas Renotte

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