Artificial neural networks versus natural neural networks. A connectionist paradigm for preference assessment

Jun Wang

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Preference is an essential ingredient in all decision processes. This paper presents a new connectionist paradigm for preference assessment in a general multicriteria decision setting. A general structure of an artificial neural network for representing two specified prototypes of preference structures is discussed. An interactive preference assessment procedure and an autonomous learning algorithm based on a novel scheme of supervised learning are proposed. Operating characteristics of the proposed paradigm are also illustrated through detailed results of numerical simulations.

Original languageEnglish
Pages (from-to)415-429
Number of pages15
JournalDecision Support Systems
Volume11
Issue number5
DOIs
Publication statusPublished - Jun 1994
Externally publishedYes

Keywords

  • Neural networks
  • Preference assessment
  • Supervised learning

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