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<p>The authors present an overview of cooperative distributed problem solving (CDPS), an emerging research area that combines aspects of AI (artificial intelligence) and distributed processing. CDPS can be used to study how a loosely coupled network of sophisticated problem-solving nodes can solve a complex problem which consists of a set of interdependent subproblems. Subproblems arise because of spatial, temporal, and functional distribution of data, knowledge, and processing capabilities. Application areas include distributed interpretation, distributed planning and control, cooperating expert systems, and computer-supported human cooperation. The authors survey the important approaches and empirical investigations that have been developed. The approaches covered include negotiation, functionally accurate cooperation, organizational structuring, multiagent planning, sophisticated local control, and theoretical frameworks.</p>
cooperative distributed problem solving; CDPS; AI; artificial intelligence; distributed processing; loosely coupled network; sophisticated problem-solving nodes; complex problem; interdependent subproblems; spatial; temporal; functional distribution; data; knowledge; processing capabilities; distributed interpretation; distributed planning; control; cooperating expert systems; computer-supported human cooperation; negotiation; functionally accurate cooperation; organizational structuring; multiagent planning; sophisticated local control; theoretical frameworks; distributed processing; knowledge engineering; problem solving
V.R. Lesser, E.H. Durfee, D.D. Corkill, "Trends in Cooperative Distributed Problem Solving", IEEE Transactions on Knowledge & Data Engineering, vol. 1, no. , pp. 63-83, March 1989, doi:10.1109/69.43404
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