Generalized Ising model for dynamic adaptation in autonomous systems

Research output: Contribution to journalArticle

16 Citations (Scopus)

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

Fingerprint

Ising model
autonomy
potential fields
configurations
statistical mechanics
vehicles
simulation
interactions

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

Cite this

@article{6f102ed2f27442ac893cf1dc240ba304,
title = "Generalized Ising model for dynamic adaptation in autonomous systems",
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.",
author = "S. Gupta and Asok Ray and Shashi Phoha",
year = "2009",
month = "8",
day = "25",
doi = "10.1209/0295-5075/87/10009",
language = "English (US)",
volume = "87",
journal = "Europhysics Letters",
issn = "0295-5075",
publisher = "IOP Publishing Ltd.",
number = "1",

}

Generalized Ising model for dynamic adaptation in autonomous systems. / Gupta, S.; Ray, Asok; Phoha, Shashi.

In: EPL, Vol. 87, No. 1, 10009, 25.08.2009.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Generalized Ising model for dynamic adaptation in autonomous systems

AU - Gupta, S.

AU - Ray, Asok

AU - Phoha, Shashi

PY - 2009/8/25

Y1 - 2009/8/25

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=79051468802&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79051468802&partnerID=8YFLogxK

U2 - 10.1209/0295-5075/87/10009

DO - 10.1209/0295-5075/87/10009

M3 - Article

VL - 87

JO - Europhysics Letters

JF - Europhysics Letters

SN - 0295-5075

IS - 1

M1 - 10009

ER -