Is MO-CMA-ES superior to NSGA-II for the evolution of multi-objective neuro-controllers?
Amiram MoshaiovOmer AbramovichPublished in: IEEE Congress on Evolutionary Computation (2014)
Keyphrases
- multi objective
- nsga ii
- evolution strategy
- evolutionary algorithm
- cma es
- multiobjective optimization
- multi objective optimization
- optimization algorithm
- pareto optimal
- multiobjective evolutionary algorithm
- differential evolution
- multi objective optimization problems
- multi objective differential evolution
- multi objective evolutionary algorithms
- genetic algorithm
- multi objective optimisation
- bi objective
- pareto dominance
- particle swarm optimization
- pareto optimal solutions
- evolutionary multiobjective optimization
- evolutionary computation
- multiple objectives
- optimization problems
- objective function
- pareto fronts
- multi objective problems
- mutation operator
- strength pareto evolutionary algorithm
- crossover operator
- evolutionary multiobjective
- covariance matrix
- reinforcement learning
- constrained multi objective optimization problems
- pareto set
- neural network
- simulated annealing
- multi criteria
- genetic programming
- optimum design
- artificial neural networks
- pareto optimal set
- fitness function
- pareto frontier
- genetic operators