Collective perception in massive, open, and heterogeneous multi-agent environment

Yiming Ye*, Steven Boies, Jiming LIU, Xun Yi

*Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review

3 Citations (Scopus)

Abstract

The web of interconnected intelligent software agents as well as intelligent hardware agents will be seamlessly embedded in everywhere of our lives and constantly sensing and reacting to the environment. The dynamic and heterogeneous interactions among these agents will provide great opportunities for agent-based services. One of the challenging issues in this agent-based service environment is the task of collective perception: how to make sense of complex sensed data at the conceptual level by a group of collaborative agents. This paper proposes a strategy for collective perception when the agents involved may not share the same knowledge representation or ontology. To avoid the syntax, semantics, and ontological complexities in communicating and understanding among agents, the synthesizing agent collects only the analyzed and categorized results from other agents in the form of a natural number or a vector of natural numbers. It then perform collective perception on top of these categorized results. An eigenspace method is proposed to model and perceive events. Experimental results are presented to show the effectiveness of our mechanism.

Original languageEnglish
Pages1175-1182
Number of pages8
DOIs
Publication statusPublished - 2002
EventProceedings of the 1st International Joint Conference on: Autonomous Agents and Multiagent Systems - Bologna, Italy
Duration: 15 Jul 200219 Jul 2002

Conference

ConferenceProceedings of the 1st International Joint Conference on: Autonomous Agents and Multiagent Systems
Country/TerritoryItaly
CityBologna
Period15/07/0219/07/02

Scopus Subject Areas

  • Engineering(all)

User-Defined Keywords

  • Collective Perception
  • Pervasive Computing

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