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Springer Reinforcement Learning for Sequential Decision Making

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Description

Explore the core mechanisms behind recent technical breakthroughs like AlphaZero, AlphaStar, and autonomous driving systems. This book from Springer provides an in-depth look at reinforcement learning (RL), a theory that enables an agent to develop self-evolution through continuous environment interactions. Understand how RL allows agents to master complex tasks, from defeating top human Go players to navigating the difficult strategy and partial information found in games like Starcraft. This text serves as a guide to the theory used to develop self-driving skills and advanced decision-making capabilities in modern artificial intelligence.

Key Features

This book by Springer covers the theory of reinforcement learning used to drive breakthroughs in artificial intelligence.

Learn how agents develop self-evolution through continuous interactions with their environment.

Study the mechanisms behind AlphaZero and its ability to defeat top human Go players.

Explore the application of RL in autonomous driving systems to develop advanced self-driving skills.

Understand how AlphaStar makes decisions in complex strategy games with partial information and difficult rules.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
06 April 2023
Listed Since
27 September 2022

Barcode

No barcode data available

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