def getAction(self, rawState, epsilon):
legalActions = rawState.getLegalActions()
legalActions.remove(Directions.STOP)
if util.flipCoin(epsilon):
return random.choice(legalActions)
else:
qValues = [(Directions.getIndex(action),
self.getQValue(rawState, action))
for action in legalActions]
qValues = sorted(qValues, key=lambda x: x[1], reverse=True)
for index, qValue in qValues:
action = Directions.fromIndex(index)
if action in legalActions:
return action
def getAction(self, rawState, epsilon):
legalActions = rawState.getLegalActions()
legalActions.remove(Directions.STOP)
qState = self.trainingRoom.featuresExtractor.getFeatures(
rawState, None)
if util.flipCoin(epsilon):
return random.choice(legalActions)
else:
qValues = list(
enumerate(self.model.model.predict(np.array([qState]))[0]))
qValues = sorted(qValues, key=lambda x: x[1], reverse=True)
for index, qValue in qValues:
action = Directions.fromIndex(index)
if action in legalActions:
return action
def getLegalActions(state):
legalActions = state.getLegalActions()
if Directions.STOP in legalActions: legalActions.remove(Directions.STOP)
return np.array([Directions.fromIndex(i) in legalActions for i in range(4)])
