Coordination in Multi-Agent Systems: Coordination Technology in Task-Oriented Environments - Couverture souple

Chen, Gang

 
9783838307237: Coordination in Multi-Agent Systems: Coordination Technology in Task-Oriented Environments
Couverture souple
ISBN 10 : 3838307232 ISBN 13 : 9783838307237
Editeur : LAP Lambert Academic Publishing, 2009

Synopsis

Coordination, as an art of managing interdependency among activities, will be extensively studied in this book under the multi-agent system paradigm. To model the information essential to agent coordination, this book proposes a Fuzzy Subjective Task Structure (FSTS) model, through which agent coordination is viewed as a Decision-Theoretic Planning problem, to which reinforcement learning can be applied. Two learning algorithms, "coarse-grained" and "fine-grained" are presented to address agent coordination at two different levels. The "coarse-grained" algorithm operates at one level and tackles hard system constraints, while the "fine-grained" at another level and for soft constraints. Besides reinforcement learning, this book also proposes a bio-inspired approach to agent coordination. A dynamic coordination model inspired by biological metabolic system is presented. Agent coordination is achieved as every agent performs iteratively a dynamic optimization process, which utilizes explicitly the global dynamics captured through the metabolic model. All research results presented in this book are experimentally evaluated to be effective and useful in practice.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Coordination, as an art of managing interdependency among activities, will be extensively studied in this book under the multi-agent system paradigm. To model the information essential to agent coordination, this book proposes a Fuzzy Subjective Task Structure (FSTS) model, through which agent coordination is viewed as a Decision-Theoretic Planning problem, to which reinforcement learning can be applied. Two learning algorithms, "coarse-grained" and "fine-grained" are presented to address agent coordination at two different levels. The "coarse-grained" algorithm operates at one level and tackles hard system constraints, while the "fine-grained" at another level and for soft constraints. Besides reinforcement learning, this book also proposes a bio-inspired approach to agent coordination. A dynamic coordination model inspired by biological metabolic system is presented. Agent coordination is achieved as every agent performs iteratively a dynamic optimization process, which utilizes explicitly the global dynamics captured through the metabolic model. All research results presented in this book are experimentally evaluated to be effective and useful in practice.

Biographie de l'auteur

Dr. Gang Chen obtained his PhD degree from Nanyang Technological University (NTU) Singapore in 2006. He is currently a visiting assistant professor at NTU. He has research interests in various aspects of distributed systems, including multi-agent systems, peer-to-peer overlay networks, and semantic web technology.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP Lambert Academic Publishing
Date d'édition
2009
Langue
anglais
ISBN 10 
3838307232
ISBN 13 
9783838307237
Reliure
Broché
Nombre de pages
196
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
4950000000000
info@krega-onlinehandel.de

Birkenweg 31
Brakel
33034
Allemagne