Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments - ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, 1996, ICMAS'96 Workshop LIOME, Kyoto, Japan, December 10, 1996 Selected Papers (Paperback, 1997 ed.)

The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Lecture Notes in Artificial Intelligence, 1221
Release date:	April 1997
First published:	1997
Editors:	Gerhard Weiss
Dimensions:	235 x 155 x 16mm (L x W x T)
Format:	Paperback
Pages:	300
Edition:	1997 ed.
ISBN-13:	978-3-540-62934-4
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-540-62934-3
Barcode:	9783540629344

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!