Publications

During the past several years, there has been a growing recognition of the threats posed by the use of shallow tunnels against both international border security and the integrity of critical facilities. This has led to the development and testing of a variety of geophysical and surveillance techniques for the detection of these clandestine tunnels. The challenges of detection of these tunnels arising from the complexity of the near surface environment, the subtlety of the tunnel signatures themselves, and the frequent siting of these tunnels in urban environments with a high level of cultural noise, have time and again shown that any single technique is not robust enough to solve the tunnel detection problem in all cases. The question then arises as to how to best combine the multiple techniques currently available to create an integrated system that results in the best chance of detecting these tunnels in a variety of clutter environments and geologies. This study utilizes Taguchi analysis with simulated sensor detection performance to address this question. The analysis results show that ambient noise has the most effect on detection performance over the effects of tunnel characteristics and geological factors.

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This efforts objective was to identify and hybridize a suite of technologies enabling the development of predictive decision aids for use principally in combat environments but also in any complex information terrain. The technologies required included formal concept analysis for knowledge representation and information operations, Peircean reasoning to support hypothesis generation, Mill's's canons to begin defining information operators that support the first two technologies and co-evolutionary game theory to provide the environment/domain to assess predictions from the reasoning engines. The intended application domain is the IED problem because of its inherent evolutionary nature. While a fully functioning integrated algorithm was not achieved the hybridization and demonstration of the technologies was accomplished and demonstration of utility provided for a number of ancillary queries.

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The work reported in this document involves a development effort to provide combat commanders and systems engineers with a capability to explore and optimize system concepts that include operational concepts as part of the design effort. An infrastructure and analytic framework has been designed and partially developed that meets a gap in systems engineering design for combat related complex systems. The system consists of three major components: The first component consists of a design environment that permits the combat commander to perform 'what-if' types of analyses in which parts of a course of action (COA) can be automated by generic system constructs. The second component consists of suites of optimization tools designed to integrate into the analytical architecture to explore the massive design space of an integrated design and operational space. These optimization tools have been selected for their utility in requirements development and operational concept development. The third component involves the design of a modeling paradigm for the complex system that takes advantage of functional definitions and the coupled state space representations, generic measures of effectiveness and performance, and a number of modeling constructs to maximize the efficiency of computer simulations. The system architecture has been developed to allow for a future extension in which the operational concept development aspects can be performed in a co-evolutionary process to ensure the most robust designs may be gleaned from the design space(s).

In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition.

This article summarizes information related to the automated course of action (COA) development effort. The information contained in this document puts the COA effort into an operational perspective that addresses command and control theory, as well as touching on the military planning concept known as effects-based operations. The sections relating to the COA effort detail the rationale behind the functional models developed and identify technologies that could support the process functions. The functional models include a section related to adversarial modeling, which adds a dynamic to the COA process that is missing in current combat simulations. The information contained in this article lays the foundation for building a unique analytic capability.