def buildExperiment(alpha, gamma, lambdaa, importance):
net=nef.Network('HandWired parameters of RL node to bias')
net.add_to_nengo()
rl = rl_sarsa.qlambda("RL", noStateVars=2, noActions=4, noValues=20, logPeriod=2000)
world = gridworld.benchmarkA("map_20x20","BenchmarkGridWorldNodeC",10000);
net.add(rl) # place them into the network
net.add(world)
# connect them together
net.connect(world.getOrigin(QLambda.topicDataIn), rl.newTerminationFor(QLambda.topicDataIn))
net.connect(rl.getOrigin(QLambda.topicDataOut), world.getTermination(QLambda.topicDataOut))
# define the parameter sources (controllable from the simulation window)
net.make_input('alpha',[alpha])
net.make_input('gamma',[gamma])
net.make_input('lambda',[lambdaa])
net.make_input('importance',[importance])
# connect signal sources to the RL node
net.connect('alpha', rl.getTermination(QLambda.topicAlpha))
net.connect('gamma', rl.getTermination(QLambda.topicGamma))
net.connect('lambda', rl.getTermination(QLambda.topicLambda))
net.connect('importance', rl.getTermination(QLambda.topicImportance))
return net
def buildExperiment(alpha, gamma, lambdaa, importance):
net = nef.Network('HandWired parameters of RL node to bias')
net.add_to_nengo()
rl = rl_sarsa.qlambda("RL",
noStateVars=2,
noActions=4,
noValues=20,
logPeriod=2000)
world = gridworld.benchmarkA("map_20x20", "BenchmarkGridWorldNodeC", 10000)
net.add(rl) # place them into the network
net.add(world)
# connect them together
net.connect(world.getOrigin(QLambda.topicDataIn),
rl.newTerminationFor(QLambda.topicDataIn))
net.connect(rl.getOrigin(QLambda.topicDataOut),
world.getTermination(QLambda.topicDataOut))
# define the parameter sources (controllable from the simulation window)
net.make_input('alpha', [alpha])
net.make_input('gamma', [gamma])
net.make_input('lambda', [lambdaa])
net.make_input('importance', [importance])
# connect signal sources to the RL node
net.connect('alpha', rl.getTermination(QLambda.topicAlpha))
net.connect('gamma', rl.getTermination(QLambda.topicGamma))
net.connect('lambda', rl.getTermination(QLambda.topicLambda))
net.connect('importance', rl.getTermination(QLambda.topicImportance))
return net
