def MultiExperiment(args):
occlusionInd = args[0][0]
occlusions = args[0][1]
predatorInd = args[1][0]
predatorHome = args[1][1]
visualRange = args[2]
simulationInd = args[3]
directory = args[4]
real = Game(XSize, YSize, occlusions=occlusions)
simulator = Game(XSize, YSize, occlusions=occlusions)
knowledge = Knowledge()
knowledge.TreeLevel = treeknowlege
knowledge.RolloutLevel = rolloutknowledge
knowledge.SmartTreeCount = smarttreecount
knowledge.SmartTreeValue = smarttreevalue
experiment = Experiment(real, simulator)
simulationDirectory = directory + '/Data/Simulation_%d' % (simulationInd)
Path(simulationDirectory).mkdir(parents=True, exist_ok=True)
_ = experiment.DiscountedReturn(occlusions,
predatorHome,
knowledge,
occlusionInd,
predatorInd,
simulationDirectory,
visualRange=visualRange)
def MultiExperiment(args):
simulationInd = args[0][0]
predatorHome = args[0][1]
directory = args[1]
real = Game(XSize, YSize)
simulator = Game(XSize, YSize)
knowledge = Knowledge()
knowledge.TreeLevel = treeknowlege
knowledge.RolloutLevel = rolloutknowledge
knowledge.SmartTreeCount = smarttreecount
knowledge.SmartTreeValue = smarttreevalue
experiment = Experiment(real, simulator)
simulationDirectory = directory + '/Data/Simulation_%d' % (simulationInd)
Path(simulationDirectory).mkdir(parents=True, exist_ok=True)
_ = experiment.DiscountedReturn(predatorHome, simulationDirectory,
knowledge)
if not real.Grid.VisualRay(
(real.AgentHome).Copy(),
(predatorHome).Copy(), occlusions)[0]:
aggregatePolicyLibrary = []
for predatorInd2 in range(5):
try:
if np.isnan(predatorHomes[predatorInd2,
simulationInd,
occlusionInd]):
continue
except:
pass
if not real.Grid.VisualRay(
(real.AgentHome).Copy(),
(predatorHomes[predatorInd2, simulationInd,
occlusionInd]).Copy(),
occlusions)[0]:
aggregatePolicyLibrary.extend(
environmentPolicies[simulationInd]
[occlusionInd][predatorInd2])
policies = aggregatePolicyLibrary
sr, gDist = experiment.DiscountedReturn(
policies, predatorHome, occlusions)
habitSurvivalRate[predatorInd, simulationInd,
occlusionInd] = sr
habitGDist[predatorInd, simulationInd, occlusionInd] = gDist
