An adaptive mutation for cartesian genetic programming using an ε-greedy strategy.
Frederico José Dias MöllerHeder Soares BernardinoStênio Sã Rosário Furtado SoaresLucas Augusto Müller de SouzaPublished in: Appl. Intell. (2023)
Keyphrases
- genetic programming
- greedy strategy
- fitness function
- evolutionary algorithm
- greedy algorithm
- genetic algorithm
- evolutionary computation
- genetic algorithm ga
- symbolic regression
- differential evolution
- mutation operator
- financial forecasting
- gene expression programming
- optimization problems
- grammar guided genetic programming
- crossover and mutation
- classification rules
- multi objective
- regression problems
- candidate solutions
- hyper heuristics
- polar coordinates
- evolutionary approaches
- evolutionary process
- adaptive learning
- crossover operator
- simulated annealing
- machine learning
- evolutionary programming
- decision trees
- clonal selection
- grammatical evolution