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Communication, Information & Navigation (CIN) | analytical modeling (am)

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Analytical Modeling (AM) is committed to a pro-technology agenda, specializing in the intelligent use of knowledge management techniques. We seek to leverage key learning methodologies and pursue improvements to the theory of discrete event control, as well as behavioral inference of cognitive animates.

Our area of expertise is in formal languages and learning systems. We have successfully modeled non-linear context sensitive grammars using finite state automata. Our techniques utilize a state-space decomposition approach, unique to our group. Furthermore, we have made great progress in software control by modeling complex software systems as finite state machines and applying discrete event control techniques to these systems. This allows us determine the effective capabilities (such as termination time) of programs before they run, thus ensuring that they do not pose a threat to the system.

We are experts in knowledge management and inference. We have developed successful algorithms for classifying targets based on acoustic sensor data by semantic analysis. We have implemented this in a mobile cognitive sensor field. We are currently adapting wavelet compression to investigate semantic source coding, a new compression scheme based on high-fidelity translation of data to finite state machines.

Current research projects include:

  • Dynamic Decision Tools
    • Urban Smart Sensors MURI (funded by ARL, ARO)
    • Language Measure Theoretic Multiobjective Optimization (funded by
  • Information Fusion
    • Bio-Molecular Biometrics Based Human Tagging Tracking and Locating Under Video Surveillance (funded by
  • Network Modeling
  • Medical Information
  • Coordination Sciences