Share Email Print
cover

Proceedings Paper

Collective agents interpolative integral (CAII) for asymmetric threat detection
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper 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 CAII. 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.

Paper Details

Date Published: 9 April 2007
PDF: 10 pages
Proc. SPIE 6571, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007, 65710I (9 April 2007); doi: 10.1117/12.718322
Show Author Affiliations
Qiuming Zhu, Univ. of Nebraska at Omaha (United States)
Stephen O'Hara, 21st Century Systems, Inc. (United States)
Michael Simon, 21st Century Systems, Inc. (United States)
Eric Lindahl, 21st Century Systems, Inc. (United States)
Plamen V. Petrov, 21st Century Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 6571:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007
Belur V. Dasarathy, Editor(s)

© SPIE. Terms of Use
Back to Top