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Books > Computing & IT > Applications of computing > Artificial intelligence
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Environments for Multi-Agent Systems - First International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers (Paperback, 2005 ed.)
Loot Price: R1,492
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Environments for Multi-Agent Systems - First International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers (Paperback, 2005 ed.)
Series: Lecture Notes in Artificial Intelligence, 3374
Expected to ship within 18 - 22 working days
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The modern ?eld of multiagent systems has developed from two main
lines of earlier research. Its practitioners generally regard it as
a form of arti?cial intelligence (AI). Some of its earliest work
was reported in a series of workshops in the US dating from1980,
revealinglyentitled, DistributedArti?cialIntelligence, andpioneers
often quoted a statement attributed to Nils Nilsson that all AI is
distributed. The locus of classical AI was what happens in the head
of a single agent, and much MAS research re?ects this heritage with
its emphasis on detailed modeling of the mental state and processes
of individual agents. From this perspective,
intelligenceisultimatelythepurviewofasinglemind,
thoughitcanbeampli?ed by appropriate interactions with other minds.
These interactions are typically mediated by structured protocols
of various sorts, modeled on human conver- tional behavior. But the
modern ?eld of MAS was not born of a single parent. A few -
searchershavepersistentlyadvocatedideasfromthe?eldofarti?ciallife(ALife).
These scientists were impressed by the complex adaptive behaviors
of commu- ties of animals (often extremely simple animals, such as
insects or even micro- ganisms). The computational models on which
they drew were often created by biologists who used them not to
solve practical engineering problems but to test their hypotheses
about the mechanisms used by natural systems. In the ar- ?cial life
model, intelligence need not reside in a single agent, but emerges
at the level of the community from the nonlinear interactions among
agents. - cause the individual agents are often subcognitive, their
interactions cannot be modeled by protocols that presume linguistic
competence."
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