Distinguishing the Leading Agents in Classification Problems Using the Entropy-Based Metric

Evgeny Kagan, Irad Ben-Gal

Research output: Contribution to journalArticlepeer-review

Abstract

The paper addresses the problem of distinguishing the leading agents in the group. The problem is considered in the framework of classification problems, where the agents in the group select the items with respect to certain properties. The suggested method of distinguishing the leading agents utilizes the connectivity between the agents and the Rokhlin distance between the subgroups of the agents. The method is illustrated by numerical examples. The method can be useful in considering the division of labor in swarm dynamics and in the analysis of the data fusion in the tasks based on the wisdom of the crowd techniques.

Original languageEnglish
Article number318
JournalEntropy
Volume26
Issue number4
DOIs
StatePublished - Apr 2024

Keywords

  • Rokhlin metric
  • classification
  • entropy
  • leading agents

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