Convergence and Asymptotic Agreement in Distributed Decision Problems,

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)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1982
Accession Number
ADA118757

Entities

People

  • John N. Tsitsiklis
  • Michael Athans

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Command And Control
  • Command And Control Systems
  • Computations
  • Control Systems
  • Covariance
  • Hilbert Space
  • Numbers
  • Probability
  • Probability Distributions
  • Random Variables
  • Real Numbers
  • Sequences
  • Social Sciences
  • Statistics
  • Theorems

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