One of the most challenging issues for the intelligent decision
systems is to effectively manage the large-scale complex
distributed environments such as computational clouds, grids, ad
hoc and P2P networks, under the different types of users, their
relations, and real-world uncertainties. In this context the IT
resources and services usually belong to different owners
(institutions, enterprises, or individuals) and are managed by
different administrators. These administrators conform to different
sets of rules and configuration directives, and can impose
different usage policies on the system users. Additionally,
uncertainties are presented in various types of information that
are incomplete, imprecise, fragmentary or overloading, which
hinders the full and precise determination of the evaluation
criteria, their subsequent and selection, the assignment scores,
and eventually the final integrated decision result.
This book presents new ideas, analysis, implementations and
evaluation of the next generation intelligent techniques for
solving complex decision problems in large-scale distributed
systems. In 15 chapters several important formulations of the
decision problems in heterogeneous environments are identified and
a review of the recent approaches, from game theoretical models and
computational intelligent techniques, such as genetic, memetic and
evolutionary algorithms, to intelligent multi-agent systems and
networking are presented. We believe that this volume will serve as
a reference for the students, researchers and industry
practitioners working in or are interested in joining
interdisciplinary works in the areas of intelligent decision
systems using emergent distributed computing paradigms. It will
also allow newcomers to grasp key concerns and potential solutions
on the selected topics."
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