ENGLISH

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

By Gerhard Weiss (eds.) , Gerhard Weiß (auth.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
1997
ISBN
3540629343, 9783540629344
DOI
10.1007/3-540-62934-3
LCC
Q325.5
Open Library ID
OL22370881M
Language
english
Format
DJVU
Filesize
4 MB (3964195 bytes)
Series
Lecture Notes in Computer Science 1221 : Lecture Notes in Artificial Intelligence
Edition
1
Pages
300\305
Topic
Education
Library
Kolxo3
DPI
300
Time added
2011-01-06 10:13:16
Artificial Intelligence (incl. Robotics); SimulatiCompilersInterpreters

Description

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.

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