The system provides anALPS extension to the open source ECJ System
Copyright 2015 by Anthony Awuley Brock University Computer Science Department Licensed under the Academic Free License version 3.0 See the file “LICENSE” for more information
The ALPS[Hornby,2006] strategy is a diversity–enhancing algorithm that works with algorithms with elements of randomness in them . It uses an age–layered population and restricts breeding and competition between individuals. ALPS ability to maintain diversity in its population is largely due to regular introduction of individuals from different fitness basins and the novel control of competition between individuals.
The implementation is based on the version 22 of the open source Evolutionary Computation system in Java developed by Sean Luke [ECJ,V22]
[Hornby,2006] Gregory Hornby. Alps: the age-layered population structure for reducing the problem of premature convergence. In Mike Cattolico, editor, GECCO, pages 815–822. ACM, 2006.
[ECJ,V22] S. Luke, G. Balan S. Paus Z. Skolicki E. Popovici J. Harrison J. Bassett R. Hubley, L. Panait and A. Chhircop. Ecj: A java-based evolutionary computation research system, version 22, 06 2000-2015. http://www.cs.gmu.edu/~eclab/projects/ecj/ [Online; Accessed: 2 April 2014]. __
The parameter files are located in the directory io/params/ and the main class is in ec.main.Run. Three tutorials have been set up and can be found in the directories
A brief introduction is given to setting up 1 and 2.
Setting up ALPS GP (see ec/app/alps/tutorial2/params/tutorial2.params).
Feature Selection ALPS is a modification of Hornby’s ALPS algorithm directed towards the selection of relevant terminals (features) in a GP tree. It uses a frequency counting system to rank the terminals. The ranked values are converted into probabilities and are used in the selection of terminals during construction of trees/sub-trees.
// Pseudocode for FSALPS procedure FSALPS GEN() AgeScheme ← SelectAgeingScheme() layers ← CreateLayers(AgeScheme) i ← SequentialLayerSelection(layers) probVector ← InitialFeatureProbabilities() while not TerminationCondition() do if BottomLayer(i) & TooOld(i) then probVector ← ComputeFeatureProbs() j ← CreateRandomGenome(probVector) else if mutation then j ← DoMutation(probVector) else if crossover then j ← DoCrossover() end if end if end if offspringIndex ← SelectSlotNextGeneration(i) j ← CreateChild(offspringIndex) EvaluateChild(j) TryMoveUp(i,j ) end while end procedure
ALPS & FSALPS : Anthony Awuley @aawuley
ECJ : Sean Luke
Project page Prof. Brian Ross
For all ECJ related supports contact Sean Luke