Field-based coordination for pervasive multiagent systems - Info and Reading Options
By Marco Mamei

"Field-based coordination for pervasive multiagent systems" was published by Springer in 2005 - Berlin, it has 241 pages and the language of the book is English.
“Field-based coordination for pervasive multiagent systems” Metadata:
- Title: ➤ Field-based coordination for pervasive multiagent systems
- Author: Marco Mamei
- Language: English
- Number of Pages: 241
- Publisher: Springer
- Publish Date: 2005
- Publish Location: Berlin
“Field-based coordination for pervasive multiagent systems” Subjects and Themes:
- Subjects: ➤ Distributed artificial intelligence - Evolutionary programming (Computer science) - Intelligent agents (Computer software) - Self-adaptive software - Ubiquitous computing - Computer networks - Artificial intelligence - Software engineering - Programmation évolutive - Systèmes adaptatifs (Informatique) - Conception - Intelligence artificielle répartie - Systèmes enfouis (Informatique) - Programmation - Informatique - Gedistribueerde gegevensverwerking - Kunstmatige intelligentie - Programmatuurtechniek - Computer software - Computer science - Computer Communication Networks - Artificial Intelligence (incl. Robotics)
Edition Specifications:
- Pagination: xii, 241 p. :
Edition Identifiers:
- The Open Library ID: OL17002904M - OL9075225W
- Library of Congress Control Number (LCCN): 2005935330
- ISBN-13: 9783540279693
- All ISBNs: 9783540279693
AI-generated Review of “Field-based coordination for pervasive multiagent systems”:
"Field-based coordination for pervasive multiagent systems" Description:
The Open Library:
More and more, software systems involve autonomous and distributed software components that have to execute and interact in open and dynamic environments, such as in pervasive, autonomous, and mobile applications. The requirements with respect to dynamics, openness, scalability, and decentralization call for new approaches to software design and development, capable of supporting spontaneous configuration, tolerating partial failures, or arranging adaptive reorganization of the whole system. Inspired by the behaviour of complex natural systems, scientists and engineers have started to adjust their mechanisms and techniques for self-organization and adaption to changing environments. In line with these considerations, Mamei and Zambonelli propose an interaction model inspired by the way masses and particles in our universe move and self-organize according to contextual information represented by gravitational and electromagnetic fields. The key idea is to have the components’ actions driven by computational force fields, generated by the components themselves or by some infrastructures, and propagated across the environment. Together with its supporting middleware infrastructure – available with additional information under http://www.agentgroup.unimore.it – this model can serve as the basis for a general purpose and widely applicable approach for the design and development of adaptive distributed applications.
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