double operator()(Individual& ind, RNG& rng, EA& ea) {
// get the phenotype (markov network):
typename EA::phenotype_type &N = ealib::phenotype(ind, ea);
// probably want to reset the RNG for the markov network:
N.reset(rng.seed());
// now, set the values of the bits in the input vector:
double f=0.0;
for(std::size_t i=0; i<128; ++i) {
// allocate space for the inputs:
std::vector<int> inputs;//(net.ninput_states(), 0);
inputs.push_back(rng.bit());
inputs.push_back(rng.bit());
// update the network n times:
N.clear();
N.update(inputs);
if(*N.begin_output() == (inputs[0] ^ inputs[1])) {
++f;
}
}
// and return some measure of fitness:
return f;
}
