Neurogenetic approach for solving dynamic programming problems

Authors:
Matheus Giovanni Pires;Ivan Nunes Da Silva
Affiliations:
State University of Feira de Santana, Department of Computer Engineering, Feira de Santana, BA, Brazil;University of São Paulo, Department of Electrical Engineering, São Carlos, SP, Brazil
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Year:
2010

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Abstract

Dynamic programming has provided a powerful approach to solve optimization problems, but its applicability has sometimes been limited because of the high computational effort required by the conventional algorithms. This paper presents an association between Hopfield networks and genetic algorithms, which cover extensive search spaces and guarantee the convergence of the system to the equilibrium points that represent feasible solutions for dynamic programming problems.