Recurrent stable neural networks seems to represent an interesting alternative to classical algorithms for the search for optimal paths in a graph. In this paper a Hopfield neural network is adopted to solve the problem of finding the shortest path between two nodes of a graph. The results obtained point out the validity of the solution proposed and its capability to adapt itself dynamically to the variations in the costs of the graph, acquiring an ''awareness'' of its structure.

OPTIMAL PATH DETERMINATION IN A GRAPH BY HOPFIELD NEURAL-NETWORK

CAVALIERI, Salvatore
;
DI STEFANO, Antonella;MIRABELLA, Orazio
1994-01-01

Abstract

Recurrent stable neural networks seems to represent an interesting alternative to classical algorithms for the search for optimal paths in a graph. In this paper a Hopfield neural network is adopted to solve the problem of finding the shortest path between two nodes of a graph. The results obtained point out the validity of the solution proposed and its capability to adapt itself dynamically to the variations in the costs of the graph, acquiring an ''awareness'' of its structure.
1994
Hopfield net, Optimization, Path searching in a graph
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/12504
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