|
gptkbp:instance_of
|
gptkb:Artificial_Intelligence
|
|
gptkbp:applies_to
|
gptkb:Artificial_Intelligence
gptkb:machine_learning
|
|
gptkbp:can_be_combined_with
|
gptkb:machine_learning
gptkb:Deep_Learning
Other Machine Learning Techniques
|
|
gptkbp:can_be_used_for
|
Model Selection
Hyperparameter Optimization
Feature Selection
|
|
gptkbp:can_create
|
gptkb:Algorithms
Functions
Models
|
|
gptkbp:developed_by
|
gptkb:John_Koza
|
|
gptkbp:has_applications_in
|
gptkb:developers
Control Systems
Signal Processing
|
|
gptkbp:has_historical_significance
|
1990s
2000s
|
|
gptkbp:has_limitations
|
Overfitting
Computational Cost
Complexity of Solutions
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Genetic Programming
|
|
gptkbp:inspired_by
|
Biological Evolution
|
|
gptkbp:involves
|
gptkb:cross
gptkb:Genetics
Selection
|
|
gptkbp:is_associated_with
|
Conferences
Research Papers
Genetic Programming Libraries
|
|
gptkbp:is_considered
|
A Subfield of AI
A Subfield of Machine Learning
|
|
gptkbp:is_evaluated_by
|
Performance Metrics
Fitness Function
|
|
gptkbp:is_influenced_by
|
gptkb:Darwinian_Evolution
Natural Selection
Genetic Theory
|
|
gptkbp:is_popular_in
|
gptkb:scientific_community
Industry Applications
|
|
gptkbp:is_related_to
|
gptkb:Artificial_Intelligence
gptkb:neural_networks
Evolutionary Computation
|
|
gptkbp:is_taught_in
|
Computer Science Courses
Data Science Courses
Artificial Intelligence Courses
|
|
gptkbp:is_used_in
|
gptkb:robotics
Bioinformatics
Finance
Game Development
|
|
gptkbp:produces
|
Computer Programs
|
|
gptkbp:used_for
|
Data Mining
Optimization Problems
Symbolic Regression
Automated Programming
|
|
gptkbp:uses
|
gptkb:Genetic_Algorithms
|
|
gptkbp:bfsParent
|
gptkb:Genetic_Algorithms
|
|
gptkbp:bfsLayer
|
5
|