Collective Agents Interpolative Integral (CAII) for asymmetric threat detection

Qiuming Zhu, Stephen O'Hara, Michael Simon, Eric Lindahl, Plamen Petrov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper presents a reasoning system that pools the judgments from a set of inference agents with information from heterogeneous sources to generate a consensus opinion that reduces uncertainty and improves knowledge quality. The system, called Collective Agents Interpolation Integral (CAII), addresses a high level data fusion problem by combining, in a mathematically sound manner, multi-models of inference in knowledge intensive multi agent architecture. Two major issues are addressed in CAU. One is the ability of the inference mechanisms to deal with hybrid data inputs from multiple information sources and map the diverse data sets to a uniform representation in an objective space of reasoning and integration. The other is the ability of the system architecture to allow the continuous and discrete outputs of a diverse set of inference agents to interact, cooperate, and integrate.

Original languageEnglish (US)
Title of host publicationMultisensor, Multisource Information Fusion
Subtitle of host publicationArchitectures, Algorithms, and Applications 2007
DOIs
StatePublished - 2007
EventMultisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007 - Orlando, FL, United States
Duration: Apr 11 2007Apr 12 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6571
ISSN (Print)0277-786X

Conference

ConferenceMultisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007
CountryUnited States
CityOrlando, FL
Period4/11/074/12/07

Keywords

  • Asymmetric threat detection
  • Information fusion
  • Intelligent agents
  • Multi-model inference
  • Uncertainty reduction

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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