Situational Behavior Modeling

Abstract

Behavior modeling for military applications needs to consider systems in which all kind of entities participate - machines, humans, human organizations (like platoons or companies) as well as such complex entities like countries, industries and societies. The variety and the structure of entities participating in behaviors in the military domain require the use of representations and tools appropriate for this kind of complexity. Ontological modeling seems to be the best match for this domain. However, there are no known results in the literature on modeling and tracking of behaviors using an ontological approach in which automatic inference over the dynamic models of behaviors can be carried out using inference tools. A behavior model can be conceptualized in a number of ways - as an abstract concept that is independent of any physical or conceptual entity, as a feature of a specific entity, or as an abstract concept that is associated with one or more physical or conceptual entities. Various knowledge representation mechanisms including State Machines, Hidden Markov Models, Petri Nets, Game Theoretic Models and Bayesian Networks have been used extensively for behavior modeling. Most of the studies have been focusing on modeling behavior of a specific type of entity. For instance, organizational behavior modeling considers an organization as a system of interrelated entities (humans) and then develops models for behavior of humans within an organization. In the approach presented in this document, behavior is treated as being associated with a situation, i.e., with a number of objects (e.g., an organization) being in some relations with each other. While situation objects will normally have some basic behaviors associated by default, they will be able to participate in complex behaviors involving multiple situation objects.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 2009
Accession Number
ADA513027

Entities

People

  • Brian Ulicny
  • Christopher J. Matheus
  • Douglas Parent
  • Jerzy Letkowski
  • Jerzy Weyman
  • Kenneth Baclaawski
  • Lena Lau
  • Mieczyslaw M. Kokar
  • Robert Dionne
  • Won Ng

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Bayesian Networks
  • Classification
  • Cognitive Science
  • Computational Science
  • Computer Languages
  • Computer Programs
  • Computers
  • Formal Languages
  • Machine Learning
  • Ontologies
  • Probability
  • Psychology
  • Reasoning
  • Situational Awareness
  • Target Recognition

Readers

  • Neural Network Machine Learning.
  • Systems Analysis and Design
  • Theoretical Analysis.

Technology Areas

  • AI & ML