Evolution of neural networks topologies and learning parameters to produce hyper-heuristics for constraint satisfaction problems uri icon

Abstract

  • This paper describes a model which constructs hyper-heuristics for variable ordering within Constraint Satisfaction Problems (CSPs) by running a genetic algorithm that evolves the topology of neural networks and some learning parameters. © 2011 Authors.

Publication date

  • August 26, 2011