Generalized Ising model for dynamic adaptation in autonomous systems

S. Gupta, A. Ray, S. Phoha

Research output: Contribution to journalArticle

19 Scopus citations

Abstract

The paper presents a concept of Statistical Mechanics for observation-based adaptation in autonomous systems, which is typically exhibited by simple biological systems. Time-critical operations of autonomous systems (e.g., unmanned undersea vehicles (UUVs)), require in situ adaptation in the original plan of action and rapid response to evolving contextual changes and situation awareness for enhanced autonomy. In this regard, a concept of dynamic plan adaptation (DPA) is formulated in the setting of a generalized Ising model (e.g., the Potts model) over a discretized configuration space, where the targets (e.g., undersea mines) are distributed. An exogenous time-dependent potential field is defined that controls the movements of the autonomous system in the configuration space, while the decision-theoretic tool for dynamic plan adaptation is built upon local neighborhood interactions. The efficacy of the DPA algorithm has been evaluated by simulation experiments that demonstrate early detection of localized neighborhood targets as compared to a conventional search method involving back and forth motions.

Original languageEnglish (US)
Article number10009
JournalEPL
Volume87
Issue number1
DOIs
StatePublished - Aug 25 2009

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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