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Dynamic, distributed constraint solving and thermodynamic theory

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Abstract

There has been an increasing recognition that a number of key computational problems require distributed solution techniques. To facilitate the creation and advancement of these techniques, researchers have developed the distributed constraint satisfaction and optimization (DCSP/DCOP) formalisms with the understanding that many critical real-world problems can be represented using them. Subsequently, these formalisms have led to the creation of numerous protocols where most ignore a critical feature of the problems they are designed to solve: the problems change over time. Dynamic variations of the DCSP and DCOP formalisms were invented to address this deficiency, but these models have received inadequate attention from the research community. A key impediment to advancing this research area is the lack of a compelling theoretical underpinning to the analysis of these problems and the evaluation of the protocols used to solve them. This work creates a mapping of the DynDCSP and DynDCOP formalisms onto thermodynamic systems. Under this mapping, it shows that these problems obey the three laws of thermodynamics. Utilizing these laws, this work develops, for the first time, a method for characterizing the impact that dynamics has on a distributed problem as well as a technique for predicting the expected performance of distributed protocols under various levels of dynamics.

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Notes

  1. Generally a distinction is drawn between CSPs and Max-CSPs, where the goal of the latter is to minimize constraint violations rather than find a complete solution. This distinction does not strongly affect our results in this paper, so we do not address it specifically here.

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Acknowledgements

We are deeply appreciative of the help of the National Science Foundation and the Air Force Research Laboratory for funding our work on this research. This material is based on research sponsored by the Air Force Research Laboratory, under agreement number FA8750-13-1-0124 and the National Science Foundation under Grant No. IIS-1350671. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory or the U.S. Government.

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  1. Tandy School of Computer Science, University of Tulsa, Tulsa, OK, USA

    Roger Mailler, Huimin Zheng & Anton Ridgway

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  1. Roger Mailler
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  2. Huimin Zheng
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  3. Anton Ridgway
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Correspondence to Roger Mailler.

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Note that this article is an expanded revision of a previous paper by the authors, [1].

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Mailler, R., Zheng, H. & Ridgway, A. Dynamic, distributed constraint solving and thermodynamic theory. Auton Agent Multi-Agent Syst 32, 188–217 (2018). https://doi.org/10.1007/s10458-017-9377-5

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