def vIteration(world, userMap, maxX, maxY, discount=0.99, MAX_ITERATIONS=100):
gen = BasicGridWorld(userMap, maxX, maxY)
domain = gen.generateDomain()
initialState = gen.getExampleState(domain);
rf = BasicRewardFunction(maxX, maxY, userMap)
tf = BasicTerminalFunction(maxX, maxY)
env = SimulatedEnvironment(domain, rf, tf, initialState)
visualizeInitialGridWorld(domain, gen, env)
hashingFactory = SimpleHashableStateFactory()
timing = defaultdict(list)
rewards = defaultdict(list)
steps = defaultdict(list)
convergence = defaultdict(list)
allStates = getAllStates(domain, rf, tf, initialState)
print("*** {} Value Iteration Analysis".format(world))
MAX_ITERATIONS = MAX_ITERATIONS
iterations = range(1, MAX_ITERATIONS + 1)
vi = ValueIteration(domain, rf, tf, discount, hashingFactory, -1, 1);
vi.setDebugCode(0)
vi.performReachabilityFrom(initialState)
vi.toggleUseCachedTransitionDynamics(False)
timing['Value'].append(0)
for nIter in iterations:
startTime = clock()
vi.runVI()
p = vi.planFromState(initialState);
endTime = clock()
timing['Value'].append((endTime-startTime)*1000)
convergence['Value'].append(vi.latestDelta)
# evaluate the policy with evalTrials roll outs
runEvals(initialState, p, rewards['Value'], steps['Value'], rf, tf, evalTrials=1)
if nIter == 1 or nIter == 50:
simpleValueFunctionVis(vi, p, initialState, domain, hashingFactory, "Value Iteration {}".format(nIter))
simpleValueFunctionVis(vi, p, initialState, domain, hashingFactory, "Value Iteration {}".format(nIter))
dumpPolicyMap(MapPrinter.printPolicyMap(allStates, p, gen.getMap()),
world + ' Value Iteration Policy Map.pkl')
dumpCSV(nIter, timing['Value'][1:], rewards['Value'], steps['Value'], convergence['Value'], world, 'Value')
rewards = defaultdict(list)
steps = defaultdict(list)
convergence = defaultdict(list)
allStates = getAllStates(domain, rf, tf, initialState)
# Value Iteration
iterations = range(1, MAX_ITERATIONS + 1)
vi = ValueIteration(domain, rf, tf, discount, hashingFactory, -1, 1)
vi.setDebugCode(0)
vi.performReachabilityFrom(initialState)
vi.toggleUseCachedTransitionDynamics(False)
print "//{} Value Iteration Analysis//".format(world)
flag = True
timing['Value'].append(0)
for nIter in iterations:
startTime = clock()
vi.runVI()
#timing['Value'].append((clock()-startTime) * 1000)
timing['Value'].append(timing['Value'][-1] + clock() - startTime)
p = vi.planFromState(initialState)
convergence['Value'].append(vi.latestDelta)
# evaluate the policy with evalTrials roll outs
runEvals(initialState, p, rewards['Value'], steps['Value'])
#if nIter == 1:
#simpleValueFunctionVis(vi, p, initialState, domain, hashingFactory, "Value Iteration {}".format(nIter))
if (vi.latestDelta < 1e-6) and flag:
flag = False
simpleValueFunctionVis(vi, p, initialState, domain, hashingFactory,
"Value Iteration {}".format(nIter))
dumpPolicyMap(
MapPrinter.printPolicyMap(allStates, p, gen.getMap()),
'Value {} Iter {} Policy Map.pkl'.format(world, nIter))
