My Account Log in

1 option

Multi-Agent Technologies and Machine Learning / edited by I. A. Sheremet.

DOAB Directory of Open Access Books Available online

View online
Format:
Book
Contributor:
Sheremet, I. A., editor.
Series:
Artificial intelligence (IntechOpen (Firm))
Artificial Intelligence
Language:
English
Subjects (All):
Artificial intelligence.
Physical Description:
1 online resource (132 pages).
Place of Publication:
London : IntechOpen, 2023.
Summary:
This book discusses multi-agent technologies (MATs) and machine learning (ML). These tools can be integrated and applied in industry, commerce, energy, medicine, psychology, and other areas. This volume consists of six chapters in three sections that discuss the integration, applications, and advanced results of MATs and ML.
Contents:
Preface
Section 1 Advanced Results in the Area of Integration of Multi-Agent Technologies and Machine Learning
Chapter 1 A State-of-the-Art Survey on Various Domains of Multi-Agent Systems and Machine Learning by Aida Huerta Barrientos and Alejandro Nila Luevano
Chapter 2 Deep Multiagent Reinforcement Learning Methods Addressing the Scalability Challenge by Theocharis Kravaris and George A. Vouros
Section 2 Applications of Multi-Agent Technologies Combined with Machine Learning
Chapter 3 Role of an Optimal Multiagent Scheduling in Different Applications Using ML by Fahmina Taranum, Sridevi K, Maniza Hijab, Syeda Fouzia Sayeedunissa, Afshan Kaleem and Niraja K.S
Chapter 4 On an Approach to Knowledge Management and the Development of the Knowledge-Based Multi-Agent System by Evgeniy Zaytsev and Elena Nurmatova
Section 3 Advanced Developments in Multi-Agent Technologies and Machine Learning Creating Potential for Their Further Integration 71
Chapter 5 Modeling Electric Vehicle Charging Station Behavior Using Multiagent System by Jaslin Shaleem Khan, Malligama Arachchige Uditha Sudheera Navaratne and Janaka Bandara Ekanayake
Chapter 6 Approximate Dynamic Programming: An Efficient Machine Learning Algorithm.
Notes:
Includes bibliographical references and index.
Description based on: online resource; title from PDF title page (IntechOpen, viewed July 01, 2023).

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account