Conference paper accepted: A Study into the Improvement of Binary Hopfield Networks for Map Coloring

The work A Study into the Improvement of Binary Hopfield Networks for Map Coloring has been published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (4432 LNCS), PART 2, pp. 98-106.

Abstract:

The map-coloring problem is a well known combinatorial optimization problem which frequently appears in mathematics, graph theory and artificial intelligence. This paper presents a study into the performance of some binary Hopfield networks with discrete dynamics for this classic problem. A number of instances have been simulated to demonstrate that only the proposed binary model provides optimal solutions. In addition, for large-scale maps an algorithm is presented to improve the local minima of the network by solving gradually growing submaps of the considered map. Simulation results for several n-region 4-color maps showed that the proposed neural algorithm converged to a correct colouring from at least 90% of initial states without the fine-tuning of parameters required in another Hopfield models. © Springer-Verlag Berlin Heidelberg 2007.

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