Title :
A neural network for path search in directed graphs
Author :
Serpen, Gursel ; Livingston, David L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA
Abstract :
The use of a Boltzmann machine to search for the shortest path in a directed graph (digraph) whose edge weights are equal is discussed. The adjacency matrix of the digraph is employed in the Boltzmann machine topology such that each entry in the adjacency matrix corresponds to a computation node of the Boltzmann machine. The quadratic performance function, for which the Boltzmann machine finds minima, is defined using the syntactic constraints that a path specification has to satisfy. An example application of the proposed method employing a 10-node digraph is demonstrated
Keywords :
directed graphs; neural nets; search problems; 10-node digraph; Boltzmann machine; adjacency matrix; computation node; directed graphs; edge weights; minima; neural network; path search; quadratic performance function; shortest path; syntactic constraints; Annealing; Computer networks; Concurrent computing; Distributed computing; Hopfield neural networks; Intelligent networks; Network topology; Neural networks; Processor scheduling; State-space methods;
Conference_Titel :
Southeastcon '90. Proceedings., IEEE
Conference_Location :
New Orleans, LA
DOI :
10.1109/SECON.1990.117877
