| The Book | Examples of agents you will learn to develop |
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 Topics Covered |
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HOIAWOG!: Your guide to developing AI agents using deep reinforcement learning. Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulator.
- Chapter 1: Introduction to Intelligent Agents and Learning Environments 👾
- Chapter 2: Reinforcement Learning and Deep Reinforcement Learning
- Chapter 3: Getting started with OpenAI Gym and Deep Reinforcement Learning
- Chapter 4: Exploring the Gym and its features
- Chapter 5: Implementing your first learning agent -- Solving the Mountain Car problem
- Chapter 6: Implementing an Intelligent Agent for Optimal Control using Deep Q Learning
- Chapter 7: Creating custom OpenAI gym environments - Carla driving simulator
- Chapter 8: Implementing an Intelligent & Autonomous Car Driving Agent using Deep Actor-Critic Algorithm
- Chapter 9: Exploring the Learning Environment Landscape: Roboschool, Gym-Retro, StarCraft-II, DeepMindLab
- Chapter 10: Exploring the Learning Algorithm Landscape: DDPG (Actor-Critic), PPO (Policy-Gradient), Rainbow (Value-based)