def __init__(self, index, offense):
DefensiveReflexAgent.__init__(self, index)
if offense:
self.myNotFeatures = [ 'eatingEnemy','distanceToClosestEnemyAsGhostSquared', 'attackingEnemyAsGhost',
'numberOfYourFoodsRemaining', 'homeTerritory', 'distanceToClosestEnemyAsGhost', 'isPacman']
else:
TrialAgent.defenseIndex.append(index)
self.myNotFeatures = [ 'distancetoClosestEnemyFoodSquared', 'gettingEaten'
'distanceToClosestEnemyAsPacmanSquared', 'attackingEnemyAsPacman',
'numberOfEnemyFoodsRemaining','distancetoClosestEnemyFood','enemyTerritory',
'distanceToClosestEnemyAsPacman','enemyGhostClose', 'distanceToFriends']
def chooseAction(self, gameState):
# we're blue for now
if self.red: return choice(gameState.getLegalActions(self.index))
enemyIndices = []
if self.red:
enemyIndices = gameState.getBlueTeamIndices()
else:
enemyIndices = gameState.getRedTeamIndices()
if self.inferenceModule.distributions == None:
self.inferenceModule.initializeDistributions(gameState, enemyIndices)
for agentIndex in enemyIndices:
self.inferenceModule.observe(gameState, self.index, agentIndex)
self.inferenceModule.elapseTime(gameState, agentIndex)
# this is just to get the distribution in a format that is displayable
distrToDisplay = []
for i in xrange(gameState.getNumAgents()):
if i in self.inferenceModule.distributions.keys():
distrToDisplay.append(self.inferenceModule.distributions[i])
else:
distrToDisplay.append(None)
self.displayDistributionsOverPositions(distrToDisplay)
return DefensiveReflexAgent.chooseAction(self, gameState)
def registerInitialState(self, gameState):
DefensiveReflexAgent.registerInitialState(self, gameState)
self.startingFood = len(self.getFoodYouAreDefending(gameState).asList())
self.theirStartingFood = len(self.getFood(gameState).asList())
if TrialAgent.firstTurn:
TrialAgent.distancer = distanceCalculator.Distancer(gameState.data.layout)
TrialAgent.manhattanDistancer = distanceCalculator.Distancer(gameState.data.layout)
# TrialAgent.manhattanDistancer.useManhattanDistances()
TrialAgent.distancer.getMazeDistances()
TrialAgent.legalPositions = gameState.getWalls().asList(False)
for pos in TrialAgent.legalPositions:
TrialAgent.legalNextPositions[pos] = self.getLegalNextPositions(gameState, pos)
TrialAgent.enemyIndices = self.getOpponents(gameState)
TrialAgent.allyIndices = self.getTeam(gameState)
self.initializeUniformly(gameState)
TrialAgent.firstTurn = False
TrialAgent.lastAgent = TrialAgent.allyIndices[len(TrialAgent.allyIndices) -1]
TrialAgent.numAllies = len(TrialAgent.allyIndices)
for ally in TrialAgent.allyIndices:
TrialAgent.currentGoal[ally] = (-1, -1)
TrialAgent.defenseIndex = list()
def __init__(self, index):
DefensiveReflexAgent.__init__(self, index)
self.agentName = 'defensiveQLearningAgent'
self.weights = None
def getBestAction(self, state):
return DefensiveReflexAgent.chooseAction(self, state)