def setGhostPosition(self, gameState, ghostPosition, index):
"""
Set the position of the ghost for this inference module to the specified
position in the supplied gameState.
Note that calling setGhostPosition does not change the position of the
ghost in the GameState object used for tracking the true progression of
the game. The code in inference.py only ever receives a deep copy of
the GameState object which is responsible for maintaining game state,
not a reference to the original object. Note also that the ghost
distance observations are stored at the time the GameState object is
created, so changing the position of the ghost will not affect the
functioning of observe.
"""
conf = game.Configuration(ghostPosition, game.Directions.STOP)
gameState.data.agentStates[index] = game.AgentState(conf, False)
return gameState
def setEnemyPosition(self, gameState, pos, enemyIndex):
foodGrid = self.getFood(gameState)
halfway = foodGrid.width / 2
conf = game.Configuration(pos, game.Directions.STOP)
# FOR THE WEIRD ERROR CHECK
if gameState.isOnRedTeam(self.index):
if pos[0] >= halfway:
isPacman = False
else:
isPacman = True
else:
if pos[0] >= halfway:
isPacman = True
else:
isPacman = False
gameState.data.agentStates[enemyIndex] = game.AgentState(conf, isPacman)
return gameState
def chooseAction(self, gameState):
# Choose an action based on evaluated values of next possible states
myPosition = gameState.getAgentPosition(self.index)
observedDistances = gameState.getAgentDistances()
newState = gameState.deepCopy()
for enemy in self.enemyIndices:
enemyPosition = gameState.getAgentPosition(enemy)
if enemyPosition:
newDistribution = util.Counter()
newDistribution[enemyPosition] = 1.0
self.enemyPositionitionDistribution[enemy] = newDistribution
else:
self.forwardStep(enemy, gameState)
self.observe(enemy, observedDistances, gameState)
for enemy in self.enemyIndices:
probablePosition = self.enemyPositionitionDistribution[enemy].argMax()
conf = game.Configuration(probablePosition, Directions.STOP)
newState.data.agentStates[enemy] = game.AgentState(conf, newState.isRed(probablePosition) != newState.isOnRedTeam(enemy))
action = self.getMaxEvaluatedAction(newState, depth=2)[1]
return action
def chooseAction(self, gameState):
global trackers
t1 = time.time()
self.enemypos[0] = trackers[0].trackPosition(self, gameState)
self.enemypos[1] = trackers[1].trackPosition(self, gameState)
simulationState = gameState.deepCopy()
#print (self.enemypos)
for i in range(len(self.enemypos)):
conf = game.Configuration(self.enemypos[i], Directions.STOP)
simulationState.data.agentStates[
self.enemies[i]] = game.AgentState(
conf,
simulationState.isRed(self.enemypos[i]) !=
simulationState.isOnRedTeam(self.enemies[i]))
move = self.expecti_maximize(simulationState, 3)[1]
t2 = time.time()
return move
def newAction(self, gameState):
"""
Base choose action. In this function we begin by updating our beliefs
and elapsing time for the beliefs. We also show our beliefs on the
screen by using the provided debugging function.
"""
myPos = gameState.getAgentPosition(self.index)
noisyDistances = gameState.getAgentDistances()
newState = gameState.deepCopy()
for enemy in self.enemies:
enemyPos = gameState.getAgentPosition(enemy)
if enemyPos:
new_belief = util.Counter()
new_belief[enemyPos] = 1.0
self.beliefs[enemy] = new_belief
else:
self.elapseTime(enemy, gameState)
self.observe(enemy, noisyDistances, gameState)
# self.displayDistributionsOverPositions(self.beliefs.values())
# Using the most probable position update the game state.
# In order to use expectimax we need to be able to have a set
# position where the enemy is starting out.
for enemy in self.enemies:
probablePosition = self.beliefs[enemy].argMax()
conf = game.Configuration(probablePosition, Directions.STOP)
newState.data.agentStates[enemy] = game.AgentState(
conf,
newState.isRed(probablePosition) !=
newState.isOnRedTeam(enemy))
# Do expectimax to depth 2 and get the best action to use. This is
# the furthest out that we could do this because of time constraints.
action = self.maxFunction(newState, depth=2)[1]
return action
def chooseAction(self, gameState):
"""
Parent action selection method.
This method update agent's map beliefs.
@param: gameState string map of game.
@returns str action with selected move direction ex. North
"""
# Distàncies als sons escoltats. Tenim una llista de 4 enters
# que representen les distàncies
noisyDistances = gameState.getAgentDistances()
newState = gameState.deepCopy()
# For any enemy agent tries to get visual contact of enemy
for enemy in self.enemies:
# None if no visual contact else enemy position tuple
enemyPos = gameState.getAgentPosition(enemy)
if enemyPos:
new_belief = util.Counter()
new_belief[enemyPos] = 1.0
self.beliefs[enemy] = new_belief
else:
# If not visual contact observe and move
self.updateBeliefs(enemy)
self.observe(enemy, noisyDistances, gameState)
for enemy in self.enemies:
prob_pos = self.beliefs[enemy].argMax()
conf = game.Configuration(prob_pos, Directions.STOP)
newState.data.agentStates[enemy] = game.AgentState(conf, newState.isRed(prob_pos) != newState.isOnRedTeam(
enemy))
# TODO imp effi
action = self.maxFunction(newState, depth=EXPECTIMAX_DEPTH)[1]
return action
def setGhostPositions(gameState, ghostPositions):
"Sets the position of all ghosts to the values in ghostPositionTuple."
for index, pos in enumerate(ghostPositions):
conf = game.Configuration(pos, game.Directions.STOP)
gameState.data.agentStates[index + 1] = game.AgentState(conf, False)
return gameState
def setGhostPositions(self, gameState, ghostPositions):
index, pos = ghostPositions
conf = game.Configuration(pos, game.Directions.STOP)
gameState.data.agentStates[index] = game.AgentState(conf, False)
return gameState
def setGhostPosition(self, state, ghostPosition, oppIndex):
"Sets the position of all ghosts to the values in ghostPositionTuple."
conf = game.Configuration(ghostPosition, game.Directions.STOP)
state.data.agentStates[oppIndex] = game.AgentState(conf, False)
return state
def chooseAction(self, gameState):
self.startTime = time.clock()
self.updateParticleFilters(gameState)
# Get list of actions, and consider more actions if it's urgent
actions = self.getGoodLegalActions(gameState, self.index)
# Check for a death, setting defensive ghosts to attack mode if so
#for i in self.enemyIndices:
# if (self.enemyLocFilters[i].getMostLikelyPos() == gameState.getInitialAgentPosition(i)
# and gameState.data.timeleft < 1147):
# print('EEOEE')
# Check if the enemy is observable, changing strategy if necessary
for i in self.enemyIndices:
self.seenEnemies = []
myPos = gameState.getAgentPosition(self.index)
exactPosition = gameState.getAgentPosition(i)
newStrat = None
if exactPosition is not None: #and self.distancer.getDistance(myPos, exactPosition) < 4:
self.seenEnemies.append(i)
newStrat = self.evalStratChange(gameState, i)
else:
newStrat = "Attack"
if newStrat is not None:
self.strategies[self.index] = newStrat
# Remove old food
foodLocs = self.getFood(gameState).asList()
for _, l in self.foodLists.iteritems():
missingFood = [l1 for l1 in l if l1 not in foodLocs]
for food in missingFood:
l.remove(food)
dist = util.Counter()
l = 'Bottom' if self.isBottom else 'Top'
for food in self.foodLists[l]:
dist[food] += 1
dist.normalize()
self.displayDistributionsOverPositions([dist])
# Get current target if chasing
if self.strategies[self.index] == 'Chase':
minDistance = None
closestEnemy = None
for e in self.seenEnemies:
distance = self.distancer.getDistance(gameState.getAgentPosition(self.index),
gameState.getAgentPosition(e))
if not closestEnemy or minDistance > distance:
minDistance = distance
closestEnemy = e
if closestEnemy is not None:
self.currentTarget = self.getTarget(gameState, closestEnemy)
dist = util.Counter()
dist[self.currentTarget] += 1
dist.normalize()
self.displayDistributionsOverPositions([dist])
# If there's only one action, just take it
if len(actions) is 1:
return actions[0]
# Create simulated game state based on estimated enemy locations
simState = gameState.deepCopy()
for i in self.enemyIndices:
if gameState.getAgentPosition(i) is None:
mostLikelyPos = self.enemyLocFilters[i].getMostLikelyPos()
conf = game.Configuration(mostLikelyPos, game.Directions.STOP)
simState.data.agentStates[i] = game.AgentState(conf, False)
bestAction = random.choice(actions)
currBestAction = self.getBestAction(simState, 2, actions)
bestAction = currBestAction
return bestAction
def setEnemyPositions(gameState, ghostPositions, enemyIndices):
"Sets the position of all ghosts to the values in ghostPositionTuple."
for i in range(len(ghostPositions)):
conf = game.Configuration(ghostPositions[i], game.Directions.STOP)
gameState.data.agentStates[enemyIndices[i]] = game.AgentState(conf, False)
return gameState
def setGhostPosition(self, gameState, ghostPosition):
conf = game.Configuration(ghostPosition, game.Directions.STOP)
gameState.data.agentStates[self.index] = game.AgentState(conf, False)
return gameState
def chooseAction(self, gameState):
self.startTime = time.clock()
self.myPos = gameState.getAgentPosition(self.index)
self.updateParticleFilters(gameState)
# Remove old food from personal lists
isFoodRemoved = False
for _, l in self.foodLists.iteritems():
missingFood = [
l1 for l1 in l if l1 not in self.getFood(gameState).asList()
]
for food in missingFood:
l.remove(food)
isFoodRemoved = True
# Compute position of the nearest food
if len(self.foodList) > 3:
self.closestFood = self.getClosestFood(self.foodList,
self.myPos)[0]
else:
self.closestFood = self.getClosestFood(
self.getFood(gameState).asList(), self.myPos)[0]
# Check if the enemy is observable
self.seenEnemies = []
for i in self.enemyIndices:
exactPosition = gameState.getAgentPosition(i)
if exactPosition is not None:
self.seenEnemies.append(i)
# Reset strategy to attack
if gameState.getAgentState(self.index).isPacman or \
self.myPos == gameState.getInitialAgentPosition(self.index) or (not self.seenEnemies and
(self.strategies[self.index] == "Chase" or self.strategies[self.index] == "Scatter")):
self.strategies[self.index] = "Attack"
# Choose whether or not to change strategy based on seen enemies
if self.seenEnemies:
newStrat = None
closestEnemyDist = None
for e in self.seenEnemies:
enemyPos = gameState.getAgentPosition(e)
dist = self.distancer.getDistance(self.myPos, enemyPos)
if not closestEnemyDist or dist < closestEnemyDist:
self.closestEnemy = e
closestEnemyDist = dist
newStrat = self.evalStratChange(gameState, self.closestEnemy)
if newStrat is not None:
self.strategies[self.index] = newStrat
# Get possible actions
if isFoodRemoved or not self.seenEnemies:
actions = self.getGoodLegalActions(gameState, self.index, True)
else:
actions = self.getGoodLegalActions(gameState, self.index)
''' debugging pellets
dist = util.Counter()
l = 'Bottom' if self.isBottom else 'Top'
for food in self.foodLists[l]:
dist[food] += 1
dist.normalize()
self.displayDistributionsOverPositions([dist])
'''
''' debugging target
dist = util.Counter()
dist[self.currentTarget] += 1
dist.normalize()
self.displayDistributionsOverPositions([dist])
'''
# If there's only one action, just take it
if len(actions) is 1:
return actions[0]
# Create simulated game state based on estimated enemy locations
simState = gameState.deepCopy()
for i in self.enemyIndices:
if gameState.getAgentPosition(i) is None:
mostLikelyPos = self.enemyLocFilters[i].getMostLikelyPos()
conf = game.Configuration(mostLikelyPos, game.Directions.STOP)
simState.data.agentStates[i] = game.AgentState(conf, False)
bestAction = random.choice(actions)
currBestAction = self.getBestAction(simState, 2, actions)
bestAction = currBestAction
return bestAction
