Zobacz książki o podobnej tematyce

Więcej informacji o Deep Reinforcement Learning

• Dane szczegółowe
• Opis
• Ulubione w innej kategorii

Za ten zakup dostaniesz 462 punkty

Opis

Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance. Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailed explanations. The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.

Szczegóły książki

Kategoria Książki po angielsku Computing & information technology Computer science Artificial intelligence

• Pełny tytuł: Deep Reinforcement Learning
• Podtytuł: Fundamentals, Research and Applications
• Autor: Hao Dong, Zihan Ding, Shanghang Zhang
• Język: Angielski
• Oprawa: Twarda
• Liczba stron: 544
• EAN: 9789811540943
• ID: 28196369
• Wydawca: Springer, Berlin
• Waga: 906 g
• Wymiary: 30 × 157 × 33 mm
• Rok wydania: 2020

Ulubione w innej kategorii

---

---

---