Deep Reinforcement Learning Hands-On

Deep Reinforcement Learning Hands-On

A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF

Lapan, Maxim

Packt Publishing Limited

11/2024

716

Mole

9781835882702

15 a 20 dias

Descrição não disponível.
Table of Contents

What Is Reinforcement Learning?
OpenAI Gym API and Gymnasium
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
Actor-Critic Methods - A2C and A3C
The TextWorld Environment
Web Navigation
Continuous Action Space
Trust Region Methods
Black-Box Optimizations in RL
Advanced Exploration
Reinforcement Learning with Human Feedback
AlphaGo Zero and MuZero
RL in Discrete Optimization
Multi-Agent RL
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