
Deep Reinforcement Learning Hands-On
Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more
Publisher:Packt Publishing Limited
By: Maxim Lapan
Paid access
|Sep 2024Table of Contents
- What Is Reinforcement Learning?
- OpenAI Gym
- Deep Learning with PyTorch
- The Cross-Entropy Method
- Tabular Learning and the Bellman Equation
- Deep Q-Networks
- Higher-Level RL libraries
- DQN Extensions
- Ways to Speed up RL
- Stocks Trading Using RL
- Policy Gradients
- The Actor-Critic Method
- Asynchronous Advantage Actor-Critic
- Training Chatbots with RL
- The TextWorld environment
- Web Navigation
- Continuous Action Space
- RL in Robotics
- Trust Regions
- Black-Box Optimization in RL
- Advanced exploration
- Beyond Model-Free
- AlphaGo Zero
- RL in Discrete Optimisation
- Multi-agent RL
PDF ISBN: 978-1-83882-004-6
Publisher: Packt Publishing Limited
Copyright owner: © 2020 Packt Publishing
Publication date: 2024
Language: English
Pages: 826
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