A comparison of three information gathering strategies in DAI systems under noisy conditions

H. R. Rao, J. C. Moore, K. Nam, Raghu Santanam, A. Whinston

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper investigates a problem of task allocation in Distributed Artificial Intelligence (DAI) systems, where a coordinator allocates tasks among multiple agents in an optimal manner. In making the task allocation, the coordinator needs to understand the preference orders of the agents for the different task bundles. The coordinator does this by adopting an information acquisition strategy that leads to an optimal system welfare. Three different information acquisition strategies are investigated here. The strategies are compared in a noisy environment for the quality of information they provide in terms of the deviation from optimal system welfare.

Original languageEnglish (US)
Pages (from-to)489-505
Number of pages17
JournalExpert Systems with Applications
Volume11
Issue number4 SPEC. ISS.
DOIs
StatePublished - 1996
Externally publishedYes

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Optimal systems
Artificial intelligence

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

Cite this

A comparison of three information gathering strategies in DAI systems under noisy conditions. / Rao, H. R.; Moore, J. C.; Nam, K.; Santanam, Raghu; Whinston, A.

In: Expert Systems with Applications, Vol. 11, No. 4 SPEC. ISS., 1996, p. 489-505.

Research output: Contribution to journalArticle

Rao, H. R. ; Moore, J. C. ; Nam, K. ; Santanam, Raghu ; Whinston, A. / A comparison of three information gathering strategies in DAI systems under noisy conditions. In: Expert Systems with Applications. 1996 ; Vol. 11, No. 4 SPEC. ISS. pp. 489-505.
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