A learning integrated framework for group problem-solving in distributed AI systems
Menon, Uday Chandran
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https://hdl.handle.net/2142/20322
Description
Title
A learning integrated framework for group problem-solving in distributed AI systems
Author(s)
Menon, Uday Chandran
Issue Date
1992
Doctoral Committee Chair(s)
Cohen, Susan
Department of Study
Business Administration
Discipline
Business Administration
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Business Administration, General
Engineering, Mechanical
Artificial Intelligence
Computer Science
Language
eng
Abstract
Problem solving activity by groups of agents is an increasingly common phenomenon in a vast variety of domains. This phenomenon may be attributed to a combination of factors: an increasing trend towards specialization of skills in narrow functional areas and increased complexity of problems which transcend functional boundaries. Coordination of this group problem solving (GPS) activity so that it is effective and coherent requires an understanding of several GPS related issues such as organization of agents, decomposability of problems, etc. This research proposes a generic framework for GPS that identifies a set of design dimensions and develops generic mechanisms for achieving the problem solving and coordination processes characterizing GPS. This framework is then used to build prototypical GPS systems in two application domains--group decision support systems (GDSS) and computer integrated manufacturing (CIM)--so that key research issues of GPS can be studied.
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