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ThinkMind // International Journal On Advances in Intelligent Systems, volume 8, numbers 3 and 4, 2015 // View article intsys_v8_n34_2015_13

A Novel Chemistry-inspired Approach to Efficient Coordination of Multi-mission Networked Objects

Authors:
Mahmoud ElGammal
Mohamed Eltoweissy

Keywords: Nature-inspired computing; Internet-of-Things; Pervasive computing; Belief propagation; Computational Chemistry

Abstract:
In this paper we present a chemistry-inspired approach for coordinating networked objects in pervasive computing environments built on the concept of chemical affinity. Our thesis is that by paralleling the model of interaction that takes place among atoms during a chemical reaction, a form of collective intelligence emerges among the objects in the network enabling them to achieve a common global objective while relying solely on preferences expressed on an individual basis. The main contribution of this paper is a novel implementation of a highly-parallelized chemical reaction execution engine that uses message passing to optimize reactant selection for multiple reaction rules simultaneously. In our method, objects in the chemical domain are represented using a probabilistic factor graph, where inter-reactant affinities are encoded in the factor nodes to guide bond formation among reactants. The problem of associating reactants with reaction rules is modeled as a Maximum-a-Posteriori (MAP) assignment problem, which we solve using the Max-Product Belief Propagation algorithm, allowing us to efficiently obtain a reactant-to-reaction assignment that maximizes the number of concurrent reactions. To evaluate our approach, we use simulation to assess the performance of the reaction execution engine in terms of execution speed and solution quality. Finally, we use the problem of resource-constrained task assignment among heterogeneous robots as a case study to present a concrete application of our approach.

Pages: 385 to 397

Copyright: Copyright (c) to authors, 2015. Used with permission.

Publication date: December 30, 2015

Published in: journal

ISSN: 1942-2679
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