This volume presents a collection of original research works by
leading specialists focusing on novel and promising approaches in
which the multi-agent system paradigm is used to support, enhance
or replace traditional approaches to solving difficult optimization
problems. The editors have invited several well-known specialists
to present their solutions, tools, and models falling under the
common denominator of the agent-based optimization. The book
consists of eight chapters covering examples of application of the
multi-agent paradigm and respective customized tools to solve
difficult optimization problems arising in different areas such as
machine learning, scheduling, transportation and, more generally,
distributed and cooperative problem solving.
General
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