Designing a phenotypic distance index for radial basis function neural networks

Authors:
Jesús González;Ignacio Rojas;Héctor Pomares;Julio Ortega
Affiliations:
Department of Computer Architecture and Computer Technology, University of Granada;Department of Computer Architecture and Computer Technology, University of Granada;Department of Computer Architecture and Computer Technology, University of Granada;Department of Computer Architecture and Computer Technology, University of Granada
Venue:
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Year:
2003

Citing 3
Cited 0

Algorithms for the maximum satisfiability problem

Computing
Genetic Algorithm versus Scatter Search and Solving Hard MAX-W-SAT Problems

IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Scatter Search with Random Walk Strategy for SAT and MAX-W-SAT Problems

Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems

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Abstract

This paper introduces the ant colonies approach for the maximum weighted satisfiability problem, namely MAX-W-SAT. We describe an ant colonies algorithm for MAX-W-SAT called AC-SAT and provide an overview of the results of the empirical tests perfmed on the hard Johnson benchmark. A comparative study of the algorithm with well known procedures for MAX-W-SAT is done and shows that AC-SAT outperforms the other evolutionary meta-heuristics especially the scatter search, which has been developed recently.