pMut = 0.3
pCross = 0.9;
popsize = 50;
maxgen = 100;
if config == 3:
t=2
pMut = 0.3
pCross = 0.9;
popsize = 30;
maxgen = 100;
simName = util.randomString(20);
net=nef.Network('Vivae - Turning controller for agent')
net.add_to_nengo()
ea = EA(maxgen,popsize,minw,maxw,genomeLen);
ea.setProbabilities(pMut,pCross);
ea.initPop();
simulator = buildExperiment(net,wa,wb,wc,visibility=False);
vivae = simulator.getControls();
expNo = round(1000000*random.random(),0); # generate some number for text file data
print expNo
f = open('data/tmp/ea_%d.txt'%expNo, 'w');
sx = Saver('ea_%d_agents.txt'%expNo); # saves best agent from actual generation during the evolution into a file
# evolution insert here
while ea.wantsEval():
print 'Gen: '+repr(ea.generation())+'/'+repr(maxgen)+' actual ind is ' +repr(ea.actualOne())+'/'+repr(popsize)+' best so far: '+repr(ea.getBestFitness());
ind = ea.getInd();
# get wa,b,c from ind genome
t = 2
pMut = 0.3
pCross = 0.9
popsize = 50
maxgen = 100
if config == 3:
t = 2
pMut = 0.4
pCross = 0.9
popsize = 20
maxgen = 100
simName = util.randomString(20)
net = nef.Network('Vivae - Turning controller for agent')
net.add_to_nengo()
ea = EA(maxgen, popsize, minw, maxw, genomeLen)
ea.setProbabilities(pMut, pCross)
ea.initPop()
simulator = buildExperiment(net, wa, wb, wc, visibility=False)
vivae = simulator.getControls()
expNo = round(1000000 * random.random(), 0)
# generate some number for text file data
print expNo
f = open('data/tmp/ea_%d.txt' % expNo, 'w')
sx = Saver('ea_%d_agents.txt' % expNo)
# saves best agent from actual generation during the evolution into a file
# evolution insert here
while ea.wantsEval():
print 'Gen: ' + repr(
ea.generation()) + '/' + repr(maxgen) + ' actual ind is ' + repr(
ea.actualOne()) + '/' + repr(popsize) + ' best so far: ' + repr(
