A tensor-based mutation operator for Neuroevolution of Augmenting Topologies (NEAT).
Aldo MarzulloClaudio StamileGiorgio TerracinaFrancesco CalimeriSabine Van HuffelPublished in: CEC (2017)
Keyphrases
- mutation operator
- network topologies
- evolutionary algorithm
- differential evolution
- genetic algorithm
- crossover operator
- premature convergence
- convergence rate
- evolutionary programming
- high order
- function optimization
- artificial neural networks
- search direction
- genetic operators
- fitness function
- crossover and mutation
- step size
- initial population
- nsga ii
- optimization method
- genetic programming
- multi objective
- multi objective optimization
- traveling salesman problem
- temporal difference
- particle swarm optimization
- population diversity
- test problems
- simulated annealing