Measurements for understanding the behavior of the genetic algorithm in dynamic environments: a case study using the Shaky Ladder Hyperplane-Defined Functions.
William RandRick L. RioloPublished in: GECCO Workshops (2005)
Keyphrases
- dynamic environments
- hyperplane
- genetic algorithm
- data points
- support vector
- feature space
- input space
- linearly independent
- support vector machine
- autonomous agents
- training samples
- mobile robot
- path planning
- incremental learning algorithm
- maximal margin
- principal components
- convex hull
- kernel function
- single agent
- data sets
- linear separability
- potential field
- linearly separable
- normal vectors
- support vectors
- changing environment
- collision free
- learning algorithm
- high dimensional
- svm classifier
- machine learning