Deep Reinforcement Learning - Aske Plaat
-40% ar kodu BOOKS
Piegāde 12-18 darba dienu laikā
30 dienu atgriešanas politika
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to ... Pilns apraksts
Jums varētu patikt arī
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How To Think About AI: A Guide For The Perplexed
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
AI Engineering: Building Applications with Foundation Models
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How to Talk to AI: (And How Not To)
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Art of Game Design: A Book of Lenses
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How Linux Works: What Every Superuser Should Know
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Hands-On Large Language Models: Language Understanding and Generation
Maarten Grootendorst, Jay Alammar
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Clean Architecture: A Craftsman's Guide to Software Structure and Design
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
World of Warcraft Chronicle, Volume 2
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-40% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Deep Learning: Foundations and Concepts
Christopher M. Bishop, Hugh Bishop
-40% ar kodu BOOKS
Piegādātāja noliktavā
Aprašymas
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world¿s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects¿ desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses on the subject of deep reinforcement learning. The aim of this book is to provide an overview of the field, at the proper level of detail for a graduate course in artificial intelligence. It covers the complete field, from the basic algorithms of Deep Q-learning, to advanced topics such as multi-agent reinforcement learning and meta learning.
Vairāk informācijas
| Autors | Aske Plaat |
|---|---|
| Izdevējs | Springer Nature Singapore |
| Izlaides gads | 2022 |
| Vāka tips | Mīkstais vāks |
| EAN | 9789811906374 |