Analysis of constraint satisfaction neural nets for route planning

Constraint satisfaction neural network simulations were used to perform route planning. Three types of models were used, schema, interactive activation competition, and Boltzmann machine, each with unique characteristics. The performances of the three models in performing routing functions were compared and analyzed, and significant factors stemming from their performance properties were identified for the exhibited differences between them.<>