Engineering Intelligent Hybrid Multi-Agent Systems

Rajiv Khosla

ISBN 10: 079239982X / ISBN 13: 9780792399827

Published by Springer Us Sep 1997, 1997

About this Item

Neuware - Engineering Intelligent Hybrid Multi-Agent Systems is about building intelligent hybrid systems. Included is coverage of applications and design concepts related to fusion systems, transformation systems and combination systems. These applications are in areas involving hybrid configurations of knowledge-based systems, case-based reasoning, fuzzy systems, artificial neural networks, genetic algorithms, and in knowledge discovery and data mining. Through examples and applications a synergy of these subjects is demonstrated. The authors introduce a multi-agent architectural theory for engineering intelligent associative hybrid systems. The architectural theory is described at both the task structure level and the computational level. This problem-solving architecture is relevant for developing knowledge agents and information agents. An enterprise-wide system modeling framework is outlined to facilitate forward and backward integration of systems developed in the knowledge, information, and data engineering layers of an organization. In the modeling process, software engineering aspects like agent oriented analysis, design and reuse are developed and described. Engineering Intelligent Hybrid Multi-Agent Systems is the first book in the field to provide details of a multi-agent architecture for building intelligent hybrid systems.

Seller Inventory # 9780792399827

Bibliographic Details

• Title: Engineering Intelligent Hybrid Multi-Agent Systems
• Publisher: Springer Us Sep 1997
• Publication Date: 1997
• Language: English
• ISBN 10: 079239982X
• ISBN 13: 9780792399827
• Binding: Buch
• Condition: Neu

About this title

Synopsis

Engineering Intelligent Hybrid Multi-Agent Systems is about building intelligent hybrid systems. Included is coverage of applications and design concepts related to fusion systems, transformation systems and combination systems. These applications are in areas involving hybrid configurations of knowledge-based systems, case-based reasoning, fuzzy systems, artificial neural networks, genetic algorithms, and in knowledge discovery and data mining. Through examples and applications a synergy of these subjects is demonstrated.
The authors introduce a multi-agent architectural theory for engineering intelligent associative hybrid systems. The architectural theory is described at both the task structure level and the computational level. This problem-solving architecture is relevant for developing knowledge agents and information agents.
An enterprise-wide system modeling framework is outlined to facilitate forward and backward integration of systems developed in the knowledge, information, and data engineering layers of an organization. In the modeling process, software engineering aspects like agent oriented analysis, design and reuse are developed and described.
Engineering Intelligent Hybrid Multi-Agent Systems is the first book in the field to provide details of a multi-agent architecture for building intelligent hybrid systems.