cma_ask — get candidate solutions from cma optimizer
X = cma_ask(es,lambda,mod) X = cma_ask(es,lambda) // the same with mod=0 X = cma_ask(es) // the same with lambda=es.sp.lambda X = %cma_ask(es) // the same
cma object from cma_new
number of column vectors to be returned
default is 0. With mod set to one, always a list of vector(s) is returned, even for lambda=1.
list of column vectors, new candidate solutions. If lambda equals to one and with default mod 0, a single vector (not a list with one vector) is returned.
clear param
param.x0 = ones(8,1);
param.sigma0 = 0.5;
es = cma_new(param);
while ~ cma_stop(es)
X = cma_ask(es); // return a list with lambda column vectors
y = []; // just in case
for i = 1:length(X) // evaluate all lambda candidate solution
y(i) = fitfun(X(i)); // must return a scalar
// re-sampling of infeasible solution if f==%nan (rejection method)
while isnan(y(i))
X(i) = cma_ask(es, 1);
y(i) = fitfun(X(i));
end
end
// do not use modified X here, unless you very well know what you do
es = cma_tell(es, X, y'); // finish iteration
end