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On Measures of Cooperation in Distributed Systems Under Uncertainties

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Abstract:

We study the evolution of distributed multiagent systems under uncertainty where the autonomous agents may cooperate with each other, and/or with supervisor/operator, in order to achieve the system's objective. The cooperation is facilitated by means of information sharing among the autonomous agents and/or supervisor/operator, which has the purpose of improving the effectiveness of the autonomous agents. The evolution of cooperative systems is modeled using discrete-state, continuous-time Markov processes. To measure and quantify the degree of cooperation within such systems, we introduce the concept of coefficient of cooperation, which is obtained by minimizing the Kullback-Leibler or 1-norm distances between nonstationary probability distributions. The presented techniques are illustrated on several different types of multiagent search systems.

Keywords: COEFFICIENT OF COOPERATION; COOPERATION; KULLBACK-LEIBLER DIVERGENCE; MARKOV PROCESSES; MULTI-AGENT SYSTEMS

Document Type: Research Article

DOI: http://dx.doi.org/10.5711/morj.15.4.39

Publication date: December 1, 2010

More about this publication?
  • Military Operations Research is the leading peer-reviewed journal publishing articles in the fields that describe operations research (OR) methodologies and theories used in key military applications.

    MOR specifically invites papers that are significant military OR applications. Of particular interest are papers that present case studies showing innovative OR applications, apply OR to major policy issues, introduce interesting new problem areas, highlight educational issues, and document the history of military OR.
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