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Proceedings Paper

A generic model of tactical plan recognition for threat assessment
Author(s): Robert Suzic
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Paper Abstract

Plan recognition has to be performed in a statistically robust manner concerning a possibly infinite number of tactical situations and different types of units. We need a generic model for tactical plan recognition where we combine observations and a priori knowledge in a flexible manner by using suitable methodologies and by having a large hypothesis space taken into account. Threat and therefore observed agent’s plans should be put into a context. Here, we propose Multi-Entity Bayesian Networks (MEBN), introduced in [2], which enable the composition of Bayesian Networks from the network pieces, as the key methodology when designing flexible plan recognition models. However, Bayesian network pieces (fragments) must be compatible and therefore we propose ontology for generic plan recognition using Bayesian network fragments. Additionally, we claim that by using multi-entity network fragments we expand the hypothesis space and using this approach various multi-agents structures can be expressed. Our final contribution is that we incorporate the use of explicit utilities in our plan recognition model.

Paper Details

Date Published: 28 March 2005
PDF: 12 pages
Proc. SPIE 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005, (28 March 2005); doi: 10.1117/12.603984
Show Author Affiliations
Robert Suzic, Swedish Defence Research Agency (Sweden)


Published in SPIE Proceedings Vol. 5813:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005
Belur V. Dasarathy, Editor(s)

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