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

776

Mole

9781835882702

Pré-lançamento - envio 15 a 20 dias após a sua edição

Descrição não disponível.
Table 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 - an Alternative
Actor-Critic Methods - A2C and A3C
The TextWorld Environment
Web Navigation
Continuous Action Space
Trust Regions - PPO, TRPO, ACKTR, and SAC
Black-Box Optimization in RL
Advanced Exploration
RL with Human Feedback
MuZero
RL in Discrete Optimization
Multi-agent RL
RL in Robotics
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