Accession Number : ADA136527
Title : Strategies of Cooperation in Distributed Problem Solving
Descriptive Note : Interim rept.
Corporate Author : RAND CORP SANTA MONICA CA
Personal Author(s) : Cammarata, Stephanie ; McArthur, David ; Steeb, Randall
Full Text : http://www.dtic.mil/get-tr-doc/pdf?AD=ADA136527
Report Date : Oct 1983
Pagination or Media Count : 38
Abstract : Distributed artificial intelligence is concerned with problem solving that is done by groups of agents. This Note describes strategies of cooperation that groups require to solve shared tasks effectively. We discuss such strategies first in a domain-independent fashion, and then in the context of a specific group problem-solving application: collision avoidance in air traffic control. We begin by contrasting the methodologies, difficulties, and opportunities of distributed and centralized problem solving. From this analysis, we infer a set of requirements on the information-gathering and organizational policies of group problem-solving agents. We then discuss a set of distributed problem solvers that we have developed in the domain of air traffic control and describe some experimental findings with the cooperative strategies used. In particular, we note large task-dependent differences in processing times, communication loads, and system errors between the several cooperative strategies.
Descriptors : *AIR TRAFFIC , *ARTIFICIAL INTELLIGENCE , *COLLISION AVOIDANCE , *DISTRIBUTED DATA PROCESSING , *PROBLEM SOLVING , CONTROL , COOPERATION , DATA ACQUISITION , DECISION MAKING , ERRORS , OPTIMIZATION , ORGANIZATIONS , POLICIES , PRODUCTIVITY , STRATEGY , TIME
Subject Categories : Computer Systems
Distribution Statement : APPROVED FOR PUBLIC RELEASE