📄 linearppp.m
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function ind=linearppp(ind,params)
%LINEARPPP Applies linear parametric parsimony pressure to a GPLAB individual.
% LINEARPPP(INDIVIDUAL,PARAMS) returns the fitness of an individual
% after applying linear parametric parsimony pressure of the form
% fitness = x * fitness + size (if lower fitness is better) or
% fitness = x * fitness - size (otherwise).
%
% Input arguments:
% INDIVIDUAL - the individual whose fitness is to change (struct)
% PARAMS - the running parameters of the algorithm (struct)
% Output arguments:
% INDIVIDUAL - the individual whose fitness was changed (1xN matrix)
%
% See also CALCFITNESS
%
% References:
% Luke, S. and Panait, L. A Comparison of Bloat Control Methods for
% Genetic Programming. Evolutionary Computation 14(3):309-344 (2006)
%
% Copyright (C) 2003-2007 Sara Silva (sara@dei.uc.pt)
% This file is part of the GPLAB Toolbox
% parameters of this tournament:
% (best cross-problem settings - see reference):
x=32;
if isempty(ind.nodes)
ind.nodes=nodes(ind.tree);
end
if params.lowerisbetter
ind.adjustedfitness=x*ind.fitness+ind.nodes;
else
ind.adjustedfitness=x*ind.fitness-ind.nodes;
end
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