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
wa = ind.m.getRange(0,16);
wb = ind.m.getRange(16,25);
wc = ind.m.getRange(25,29);
#simName = util.randomString(20);
fitness = evalInd(net,simulator,ind);
ind.getFitness().set(fitness);
print 'Ind: '+repr(ea.actualOne())+' AVG Speed is: '+repr(fitness) +' fitness is: '+repr(ind.getFitness().get());
# evaluated the last individual in the generatio? write stats
if (ea.actualOne() == (popsize-1)):
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)
print "starting build"
expNo = round(1000000 * random.random(), 0)
# generate some number for text file data
print expNo
f = open("data/ea_%d.txt" % expNo, "w")
# 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
wa = ind.m.getRange(0, 16)
wb = ind.m.getRange(16, 25)
wc = ind.m.getRange(25, 29)
# simName = util.randomString(20);
fitness = evalInd(net, simulator, ind)
ind.getFitness().set(fitness)
print "Ind: " + repr(ea.actualOne()) + " AVG Speed is: " + repr(fitness) + " fitness is: " + repr(
ind.getFitness().get()
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
wa = ind.m.getRange(0, 16)
wb = ind.m.getRange(16, 25)
wc = ind.m.getRange(25, 29)
#simName = util.randomString(20);
fitness = evalInd(net, simulator, ind)
ind.getFitness().set(fitness)
print 'Ind: ' + repr(ea.actualOne()) + ' AVG Speed is: ' + repr(
fitness) + ' fitness is: ' + repr(ind.getFitness().get())
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
wa = ind.m.getRange(0,16);
wb = ind.m.getRange(16,25);
wc = ind.m.getRange(25,29);
#simName = util.randomString(20);
fitness = evalInd(net,simulator,ind);
ind.getFitness().set(fitness);
print 'Ind: '+repr(ea.actualOne())+' AVG Speed is: '+repr(fitness) +' fitness is: '+repr(ind.getFitness().get());
# evaluated the last individual in the generatio? write stats
if (ea.actualOne() == (popsize-1)):
