def __init__(self, index, mdp, discountRate=0.9, iters=100, **kwargs):
super().__init__(index)
self.mdp = mdp
self.discountRate = discountRate
self.iters = iters
self.values = counter.Counter() # A Counter is a dict with default 0
# Compute the values here.
# Number of iterations
for i in range(self.iters):
values_temp = copy.deepcopy(self.values)
for state in self.mdp.getStates():
Qvalue = counter.Counter()
if self.mdp.isTerminal(state):
continue
# Qvalue = counter.Counter()
for action in self.mdp.getPossibleActions(state):
for nextState, prob in self.mdp.getTransitionStatesAndProbs(
state, action):
R = self.mdp.getReward(state, action, nextState)
discount = self.discountRate
Qvalue[action] += prob * (R +
(discount *
(values_temp[nextState])))
self.values[state] = Qvalue[Qvalue.argMax()]
def __init__(self, index,
extractor='pacai.core.featureExtractors.IdentityExtractor', **kwargs):
super().__init__(index, **kwargs)
self.featExtractor = reflection.qualifiedImport(extractor)
# You might want to initialize weights here.
self.weights = counter.Counter()
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
features['successorScore'] = self.getScore(successor)
myPos = successor.getAgentState(self.index).getPosition()
# Compute distance to the nearest Capsule #
capsules = self.getCapsules(gameState)
if len(capsules) > 0:
capDistance = min(
[self.getMazeDistance(myPos, capsule) for capsule in capsules])
features['capsuleDistance'] = capDistance
else:
features['capsuleDistance'] = 0
# Compute distance to nearest ghost (usually a defender goalie) #
# enemies = [gameState.getAgentState(i) for i in self.getOpponents(gameState)]
# chasers = [a for a in enemies if not a.isPacman() and a.getPosition() is not None]
# uncomment this for invader information
# invaders = [a for a in enemies if a.isPacman() and a.getPosition() is not None]
# Compute distance to the nearest food.
foodList = self.getFood(successor).asList()
if (len(foodList) > 0):
minDist = min(
[self.getMazeDistance(myPos, food) for food in foodList])
features['DistanceToFoodTarget'] = minDist
return features
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
features['successorScore'] = self.getScore(successor)
food = self.getFood(successor)
foodList = food.asList()
if (len(foodList) > 0):
myPos = successor.getAgentState(self.index).getPosition()
minDistance = min(
[self.getMazeDistance(myPos, food) for food in foodList])
features['distanceToFood'] = minDistance
opponents = self.getOpponents(gameState)
agentState = gameState.getAgentState(self.index)
myPos = agentState.getPosition()
closeGhosts = 0
for opponent in opponents:
opponentPos = gameState.getAgentState(opponent).getPosition()
if self.getMazeDistance(myPos, opponentPos) < 2:
closeGhosts += 1
features['closeGhosts'] = closeGhosts
foodAtMyPos = food[int(myPos[0])][int(myPos[1])]
if not closeGhosts and foodAtMyPos:
features['eatFood'] = 1.0
return features
def getFeatures(self, state, action):
# Extract the grid of food and wall locations and get the ghost locations.
food = state.getFood()
walls = state.getWalls()
ghosts = state.getGhostPositions()
features = counter.Counter()
features["bias"] = 1.0
# Compute the location of pacman after he takes the action.
x, y = state.getPacmanPosition()
dx, dy = Actions.directionToVector(action)
next_x, next_y = int(x + dx), int(y + dy)
# Count the number of ghosts 1-step away.
features["#-of-ghosts-1-step-away"] = sum(
(next_x, next_y) in Actions.getLegalNeighbors(g, walls)
for g in ghosts)
# If there is no danger of ghosts then add the food feature.
if not features["#-of-ghosts-1-step-away"] and food[next_x][next_y]:
features["eats-food"] = 1.0
prob = AnyFoodSearchProblem(state, start=(next_x, next_y))
dist = len(search.bfs(prob))
if dist is not None:
# Make the distance a number less than one otherwise the update will diverge wildly.
features["closest-food"] = float(dist) / (walls.getWidth() *
walls.getHeight())
features.divideAll(10.0)
return features
def __init__(self, index, mdp, discountRate=0.9, iters=100, **kwargs):
super().__init__(index, **kwargs)
self.mdp = mdp
self.discountRate = discountRate
self.iters = iters
self.values = counter.Counter() # A Counter is a dict with default 0
# Compute the values here.
states = mdp.getStates()
for i in range(iters):
vals = counter.Counter()
for state in states:
action = self.getAction(state)
if action:
vals[state] = self.getQValue(state, action)
self.values = vals
def __init__(self, index, mdp, discountRate=0.9, iters=100, **kwargs):
super().__init__(index)
self.mdp = mdp
self.discountRate = discountRate
self.iters = iters
self.values = counter.Counter() # A Counter is a dict with default 0
# Compute the values here.
# FIXME: can be more efficient, getQValue is called twice.
for i in range(iters):
newVals = counter.Counter()
for state in mdp.getStates():
bestAction = self.getAction(state)
if bestAction is not None:
newVals[state] = self.getQValue(state, bestAction)
self.values = newVals.copy()
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = gameState
myState = successor.getAgentState(self.index)
myPos = myState.getPosition()
# Computes whether we're on defense (1) or offense (0).
features['onDefense'] = 1
if (myState.isPacman()):
features['onDefense'] = 0
features['successorScore'] = 0
features['distanceToFood'] = 0
# Computes distance to invaders we can see.
enemies = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
invaders = [
a for a in enemies if a.isPacman() and a.getPosition() is not None
]
features['numInvaders'] = len(invaders)
if (len(invaders) > 0):
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in invaders
]
features['invaderDistance'] = min(dists)
features['onDefense'] = 1
else:
features['onDefense'] = 0
myPos = successor.getAgentState(self.index).getPosition()
foodList = self.getFood(successor).asList()
minDistance = min(
[self.getMazeDistance(myPos, food) for food in foodList])
features['distanceToFood'] = minDistance
features['successorScore'] = self.getScore(successor)
features['invaderDistance'] = 0
team = []
if successor.isOnBlueTeam(self.index):
team = successor.getBlueTeamIndices()
else:
team = successor.getRedTeamIndices()
teammate = -1
for num in team:
if num != self.index:
teammate = num
otherAgent = successor.getAgentState(teammate)
otherPos = otherAgent.getPosition()
teamDist = self.getMazeDistance(myPos, otherPos)
if teamDist == 0:
features['teammateDist'] = 10
else:
features['teammateDist'] = 1 / teamDist
return features
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
myState = successor.getAgentState(self.index)
myPos = myState.getPosition()
# Computes whether we're on defense (1) or offense (0).
features['onDefense'] = 1
if (myState.isPacman()):
features['onDefense'] = 0
else:
features['isGhost'] = 1
# Computes distance to invaders we can see.
enemies = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
invaders = [
a for a in enemies if a.isPacman() and a.getPosition() is not None
]
features['numInvaders'] = len(invaders)
if (len(invaders) > 0):
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in invaders
]
features['invaderDistance'] = min(dists)
if min(dists) <= 1 and successor.getAgentState(
self.index).isScared():
features['suicide'] = 1
enemies = self.getOpponents(gameState)
defenders = []
attackers = []
d = 0
for enemy in enemies:
if gameState.getAgentState(enemy).isPacman():
attackers.append(gameState.getAgentState(enemy))
global assumedAttacker
assumedAttacker = enemy
global test
test = 1
else:
defenders.append(gameState.getAgentState(enemy))
d = enemy
# Make defender not wait right on border
if test == 1 and len(attackers) == 0:
attackerState = successor.getAgentState(assumedAttacker)
attPos = attackerState.getPosition()
targetDest = midpointTiles[int(attPos[1])]
features['chaser'] = self.getMazeDistance(targetDest, myPos)
if len(attackers) == 0 and test == 0:
attackerState = successor.getAgentState(d)
attPos = attackerState.getPosition()
targetDest = midpointTiles[int(attPos[1])]
features['chaser'] = self.getMazeDistance(targetDest, myPos)
return features
def getPolicy(self, state):
# FIXME: not sure if this is even needed
if self.mdp.isTerminal(state):
return None
memo = counter.Counter()
for action in self.mdp.getPossibleActions(state):
memo[action] = self.getQValue(state, action)
return memo.argMax()
def displayValues(self, agent, currentState=None, message='Agent Values'):
values = counter.Counter()
policy = {}
states = self.gridworld.getStates()
for state in states:
values[state] = agent.getValue(state)
policy[state] = agent.getPolicy(state)
drawValues(self.gridworld, values, policy, currentState, message)
utils.sleep(0.05 / self.speed)
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
myState = successor.getAgentState(self.index)
myPos = myState.getPosition()
# Computes whether we're on defense (1) or offense (0).
features['onDefense'] = 1
if (myState.isPacman()):
features['onDefense'] = 0
enemies = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
# Compute distance to nearest ghost (before it is invading)
ghosts = [
a for a in enemies
if not a.isPacman() and a.getPosition() is not None
]
if len(ghosts) > 0:
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in ghosts
]
features['ghostDist'] = min(dists)
# Computes distance to invaders we can see.
invaders = [
a for a in enemies if a.isPacman() and a.getPosition() is not None
]
features['numInvaders'] = len(invaders)
if (len(invaders) > 0):
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in invaders
]
features['invaderDistance'] = min(dists)
""" # Abbas put this in here for some reason, it doesn't seem to do anything yet
closestDistance = dists[0]
position = [a.getPosition() for a in invaders]
closestPosition = position[0]
for i in range(len(dists)):
if dists[i] < closestDistance:
closestDistance = dists[i]
closestPosition = position[i]
"""
if (action == Directions.STOP):
features['stop'] = 1
rev = Directions.REVERSE[gameState.getAgentState(
self.index).getDirection()]
if (action == rev):
features['reverse'] = 1
return features
def __init__(self, index, mdp, discountRate=0.9, iters=100, **kwargs):
super().__init__(index)
self.mdp = mdp
self.discountRate = discountRate
self.iters = iters
self.values = counter.Counter() # A Counter is a dict with default 0
# Compute the values here.
raise NotImplementedError()
def displayNullValues(self, currentState=None, message=''):
values = counter.Counter()
# policy = {}
states = self.gridworld.getStates()
for state in states:
values[state] = 0.0
# policy[state] = agent.getPolicy(state)
drawNullValues(self.gridworld, currentState, '')
# drawValues(self.gridworld, values, policy, currentState, message)
utils.sleep(0.05 / self.speed)
def displayQValues(self,
agent,
currentState=None,
message='Agent Q-Values'):
qValues = counter.Counter()
states = self.gridworld.getStates()
for state in states:
for action in self.gridworld.getPossibleActions(state):
qValues[(state, action)] = agent.getQValue(state, action)
drawQValues(self.gridworld, qValues, currentState, message)
utils.sleep(0.05 / self.speed)
def getPolicy(self, state):
if self.mdp.isTerminal(state):
return None
possibleActions = self.mdp.getPossibleActions(state)
Qvalue = counter.Counter()
for action in possibleActions:
Qvalue[action] = self.getQValue(state, action)
return Qvalue.argMax()
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
myState = successor.getAgentState(self.index)
myPos = myState.getPosition()
borders = successor.getWalls()
midWidth = math.floor(borders.getWidth() / 2)
yValue = random.randint(0, borders.getHeight() - 1)
midPoint = (midWidth, yValue)
while successor.hasWall(midWidth, yValue):
yValue = random.randint(0, borders.getHeight() - 1)
midPoint = (midWidth, yValue)
# Computes whether we're on defense (1) or offense (0).
features['onDefense'] = 1
if (myState.isPacman()):
features['onDefense'] = 0
# Computes distance to invaders we can see.
enemies = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
invaders = [
a for a in enemies if a.isPacman() and a.getPosition() is not None
]
features['numInvaders'] = len(invaders)
if len(invaders) == 0:
distanceToMid = self.getMazeDistance(myPos, midPoint)
features['distanceToMiddle'] = distanceToMid
else:
features['distanceToMiddle'] = 0
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in invaders
]
features['invaderDistance'] = min(dists)
if (action == Directions.STOP):
features['stop'] = 1
rev = Directions.REVERSE[gameState.getAgentState(
self.index).getDirection()]
if (action == rev):
features['reverse'] = 1
return features
def drawQValues(gridworld,
qValues,
currentState=None,
message='State-Action Q-Values'):
grid = gridworld.grid
blank()
stateCrossActions = [[(state, action)
for action in gridworld.getPossibleActions(state)]
for state in gridworld.getStates()]
qStates = functools.reduce(lambda x, y: x + y, stateCrossActions, [])
qValueList = [qValues[(state, action)]
for state, action in qStates] + [0.0]
minValue = min(qValueList)
maxValue = max(qValueList)
for x in range(grid.width):
for y in range(grid.height):
state = (x, y)
gridType = grid[x][y]
isExit = (str(gridType) != gridType)
isCurrent = (currentState == state)
actions = gridworld.getPossibleActions(state)
if (actions is None or len(actions) == 0):
actions = [None]
q = counter.Counter()
valStrings = {}
for action in actions:
v = qValues[(state, action)]
q[action] += v
valStrings[action] = '%.2f' % v
if gridType == '#':
drawSquare(x, y, 0, 0, 0, None, None, True, False, isCurrent)
elif isExit:
action = 'exit'
value = q[action]
valString = '%.2f' % value
drawSquare(x, y, value, minValue, maxValue, valString, action,
False, isExit, isCurrent)
else:
drawSquareQ(x, y, q, minValue, maxValue, valStrings, actions,
isCurrent)
pos = to_screen(((grid.width - 1.0) / 2.0, -0.8))
utils.text(pos, TEXT_COLOR, message, "Courier", -32, "bold", "c")
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
features['successorScore'] = self.getScore(successor)
# Compute distance to the nearest food.
foodList = self.getFood(successor).asList()
# This should always be True, but better safe than sorry.
if (len(foodList) > 0):
myPos = successor.getAgentState(self.index).getPosition()
minDistance = min([self.getMazeDistance(myPos, food) for food in foodList])
features['distanceToFood'] = minDistance
return features
def __init__(self, index, mdp, discountRate = 0.9, iters = 100, **kwargs):
super().__init__(index)
self.mdp = mdp
self.discountRate = discountRate
self.iters = iters
self.values = counter.Counter() # A Counter is a dict with default 0
copyOfValues = self.values.copy()
for i in range(self.iters):
states = self.mdp.getStates()
for state in states:
if not self.mdp.isTerminal(state):
move = self.getPolicy(state)
qValue = self.getQValue(state, move)
copyOfValues[state] = qValue
for state in states:
self.values[state] = copyOfValues[state]
def getFeatures(self, agent, gameState, action):
features = counter.Counter()
successor = gameState
features['successorScore'] = self.getScore(successor)
food = self.getFood(successor)
foodList = food.asList()
if (len(foodList) > 0):
myPos = successor.getAgentState(self.index).getPosition()
minDistance = min(
[self.getMazeDistance(myPos, food) for food in foodList])
features['distanceToFood'] = minDistance
opponents = self.getOpponents(gameState)
agentState = gameState.getAgentState(self.index)
myPos = agentState.getPosition()
closeGhosts = 0
for opponent in opponents:
opponentPos = gameState.getAgentState(opponent).getPosition()
if self.getMazeDistance(myPos, opponentPos) < 2:
closeGhosts += 1
features['closeGhosts'] = closeGhosts
foodAtMyPos = food[int(myPos[0])][int(myPos[1])]
if not closeGhosts and foodAtMyPos:
features['eatFood'] = 1.0
# ATTACK FEATURE
capsules = self.getCapsules(gameState)
powerPills = [self.getMazeDistance(myPos, pill) for pill in capsules]
if len(powerPills) > 0:
eatPill = min(powerPills)
else:
eatPill = 0
if closeGhosts > 0:
features['eatPill'] = eatPill
features['eatFood'] = 0
else:
features['eatPill'] = 0
return features
def getDistribution(self, state):
# Read variables from state.
ghostState = state.getGhostState(self.index)
legalActions = state.getLegalActions(self.index)
pos = state.getGhostPosition(self.index)
isScared = ghostState.isScared()
speed = 1
if (isScared):
speed = 0.5
actionVectors = [
Actions.directionToVector(a, speed) for a in legalActions
]
newPositions = [(pos[0] + a[0], pos[1] + a[1]) for a in actionVectors]
pacmanPosition = state.getPacmanPosition()
# Select best actions given the state.
distancesToPacman = [
distance.manhattan(pos, pacmanPosition) for pos in newPositions
]
if (isScared):
bestScore = max(distancesToPacman)
bestProb = self.prob_scaredFlee
else:
bestScore = min(distancesToPacman)
bestProb = self.prob_attack
zipActions = zip(legalActions, distancesToPacman)
bestActions = [
action for action, distance in zipActions if distance == bestScore
]
# Construct distribution.
dist = counter.Counter()
for a in bestActions:
dist[a] = float(bestProb) / len(bestActions)
for a in legalActions:
dist[a] += float(1 - bestProb) / len(legalActions)
dist.normalize()
return dist
def getFeatures(self, state, action):
features = counter.Counter()
successor = self.getSuccessor(state, action)
myState = successor.getAgentState(self.index)
myPos = myState.getPosition()
# Computes whether we're on defense (1) or offense (0).
features['onDefense'] = 1
if (myState.isPacman()):
features['onDefense'] = 0
# Computes distance to invaders we can see.
enemies = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
invaders = [
a for a in enemies if a.isPacman() and a.getPosition() is not None
]
features['numInvaders'] = len(invaders)
if (len(invaders) > 0):
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in invaders
]
features['invaderDistance'] = min(dists)
else:
if state.isOnBlueTeam(self.index):
foods = state.getBlueFood().asList()
features['stayFront'] = self.getMazeDistance(myPos, foods[0])
else:
foods = state.getRedFood().asList()
features['stayFront'] = self.getMazeDistance(myPos, foods[-1])
if (action == Directions.STOP):
features['stop'] = 1
rev = Directions.REVERSE[state.getAgentState(
self.index).getDirection()]
if (action == rev):
features['reverse'] = 1
return features
def getFeatures(self, state):
food = self.getFood(state)
capsules = self.getCapsules(state)
features = counter.Counter()
features['score'] = self.getScore(state)
opponents = self.getOpponents(state)
myState = state.getAgentState(self.index)
myPos = myState.getPosition()
closeGhosts = 0
for opponent in opponents:
opponentPos = state.getAgentState(opponent).getPosition()
if self.getMazeDistance(myPos, opponentPos) < 2:
closeGhosts += 1
features['#-of-ghosts-1-step-away'] = closeGhosts
foodAtMyPos = food[int(myPos[0])][int(myPos[1])]
if not closeGhosts and foodAtMyPos:
features['eats-food'] = 10.0
foodDist = []
for x in range(food.getWidth()):
for y in range(food.getHeight()):
if food[x][y]:
foodDist.append(self.getMazeDistance(myPos, (x, y)))
features['closest-food'] = min(foodDist)
# ATTACK FEATURE
powerPills = [self.getMazeDistance(myPos, pill) for pill in capsules]
if len(powerPills) > 0:
eatPill = min(powerPills)
else:
eatPill = 0
if closeGhosts > 0:
features['eat-Pill'] = eatPill
features['eats-food'] = 0
else:
features['eat-Pill'] = 0
return features
def getFeatures(self, gameState, action):
features = counter.Counter()
successor = self.getSuccessor(gameState, action)
agentState = successor.getAgentState(self.index)
agentPos = agentState.getPosition()
# Computes whether we're on defense (1) or offense (0).
features['onDefense'] = 1
if (agentState.isPacman()):
features['onDefense'] = 0
# Computes distance to invaders we can see.
opponents = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
enemies = [
opponent for opponent in opponents
if opponent.getPosition() is not None
]
invaders = [enemy for enemy in enemies if enemy.isPacman()]
if (len(enemies) > 0):
dists = [
self.getMazeDistance(agentPos, a.getPosition())
for a in enemies
]
features['invaderDistance'] = min(dists)
elif (len(invaders) > 0):
dists = [
self.getMazeDistance(agentPos, a.getPosition())
for a in invaders
]
features['invaderDistance'] = min(dists)
rev = Directions.REVERSE[gameState.getAgentState(
self.index).getDirection()]
if (action == rev):
features['reverse'] = 1
return features
def getFeatures(self, gameState):
features = counter.Counter()
features['successorScore'] = self.getScore(gameState)
# FIXME: extract more features here.
myPos = gameState.getAgentState(self.index).getPosition()
# Compute distance to the nearest food.
foodList = self.getFood(gameState).asList()
if (len(foodList) > 0):
minDist = min(
[self.getMazeDistance(myPos, food) for food in foodList])
features['DistanceToFoodTarget'] = minDist
# Compute distance to the nearest Capsule #
capsules = self.getCapsules(gameState)
if len(capsules) > 0:
capDistance = min(
[self.getMazeDistance(myPos, capsule) for capsule in capsules])
features['capsuleDistance'] = capDistance
else:
features['capsuleDistance'] = 0
return features
def normalize(vectorOrCounter):
"""
Normalize a vector or counter by dividing each value by the sum of all values.
"""
normalizedCounter = counter.Counter()
if type(vectorOrCounter) == type(normalizedCounter):
counterContainer = vectorOrCounter
total = float(counterContainer.totalCount())
if total == 0:
return counterContainer
for key in list(counter.keys()):
value = counter[key]
normalizedCounter[key] = value / total
return normalizedCounter
else:
vector = vectorOrCounter
s = float(sum(vector))
if s == 0:
return vector
return [el / s for el in vector]
def getDistribution(self, state):
dist = counter.Counter()
for a in state.getLegalActions(self.index):
dist[a] = 1.0
dist.normalize()
return dist
def evaluationFunction(self, agent, gameState, action):
weights = counter.Counter(self.getWeights(gameState))
features = self.getFeatures(agent, gameState, action)
return weights * features
def getFeatures(self, agent, gameState, action):
features = counter.Counter()
if self.offense:
# successor = self.getSuccessor(agent, gameState, action)
successor = gameState
features['successorScore'] = self.getScore(successor)
food = self.getFood(successor)
foodList = food.asList()
if (len(foodList) > 0):
myPos = successor.getAgentState(self.index).getPosition()
minDistance = min(
[self.getMazeDistance(myPos, food) for food in foodList])
features['distanceToFood'] = minDistance
opponents = self.getOpponents(gameState)
agentState = gameState.getAgentState(self.index)
myPos = agentState.getPosition()
closeGhosts = 0
for opponent in opponents:
opponentPos = gameState.getAgentState(opponent).getPosition()
if self.getMazeDistance(myPos, opponentPos) < 2:
closeGhosts += 1
features['closeGhosts'] = closeGhosts
foodAtMyPos = food[int(myPos[0])][int(myPos[1])]
if not closeGhosts and foodAtMyPos:
features['eatFood'] = 1.0
# ATTACK FEATURE
capsules = self.getCapsules(gameState)
powerPills = [
self.getMazeDistance(myPos, pill) for pill in capsules
]
if len(powerPills) > 0:
eatPill = min(powerPills)
else:
eatPill = 0
if closeGhosts > 0:
features['eatPill'] = eatPill
features['eatFood'] = 0
else:
features['eatPill'] = 0
return features
'''
Defense features
'''
# successor = self.getSuccessor(agent, gameState, action)
successor = gameState
myState = successor.getAgentState(self.index)
myPos = myState.getPosition()
features['onDefense'] = 1
if (myState.isPacman()):
features['onDefense'] = 0
enemies = [
successor.getAgentState(i) for i in self.getOpponents(successor)
]
invaders = [
a for a in enemies if a.isPacman() and a.getPosition() is not None
]
features['numInvaders'] = len(invaders)
if (len(invaders) > 0):
dists = [
self.getMazeDistance(myPos, a.getPosition()) for a in invaders
]
features['invaderDistance'] = min(dists)
if (action == Directions.STOP):
features['stop'] = 1
rev = Directions.REVERSE[gameState.getAgentState(
self.index).getDirection()]
if (action == rev):
features['reverse'] = 1
return features