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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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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.)
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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.)
Series: Lecture Notes in Artificial Intelligence, 1221
Expected to ship within 10 - 15 working days
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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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