
Accession Number : ADA113602
Title : Convergence and Asymptotic Agreement in Distributed Decision Problems,
Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS
Personal Author(s) : Tsitsiklis,John N ; Athans,Michael
PDF Url : ADA113602
Report Date : Mar 1982
Pagination or Media Count : 21
Abstract : We consider a distributed team decision problem in which different agents obtain from the environment different stochastic measurements, possibly at different random times, related to the same uncertain random vector. Each agent has the same objective function and prior probability distribution. We assume that each agent can compute an optimal tentative decision based upon his own observation and that these tentative decisions are communicated and received, possibly at random times, by a subset of other agents. Conditions for asymptotic convergence of each agent's decision sequence and asymptotic agreement of all agents' decisions are derived. (Author)
Descriptors : *Decision theory, *Probability distribution functions, Convergence, Asymptotic normality, Decision making, Stochastic processes, Random variables, theorems
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE