def chooseCapsules(self, gameState, capsule_limit, opponent_evidences):
width, height = gameState.data.layout.width, gameState.data.layout.height
left_caps, right_caps = [], []
while len(left_caps) < (capsule_limit / 2):
x = random.randint(1, (width / 2) - 1)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
if self.isRed:
if len(left_caps) % 2 == 0:
left_caps.append(ArmourCapsule(x, y))
else:
left_caps.append(JuggernautCapsule(x, y))
else:
if len(left_caps) % 2 == 0:
left_caps.append(SonarCapsule(x, y))
else:
left_caps.append(ScareCapsule(x, y))
while len(right_caps) < (capsule_limit / 2):
x = random.randint(1, (width / 2) - 1)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
if self.isRed:
if len(right_caps) % 2 == 0:
right_caps.append(SonarCapsule(x, y))
else:
right_caps.append(ScareCapsule(x, y))
else:
if len(left_caps) % 2 == 0:
right_caps.append(ArmourCapsule(x, y))
else:
right_caps.append(JuggernautCapsule(x, y))
return left_caps + right_caps
def chooseCapsules(self, gameState, capsuleLimit, opponentEvidences):
net = contestPowersBayesNet.powersBayesNet()
leftCapsules = []
rightCapsules = []
width, height = gameState.data.layout.width, gameState.data.layout.height
for i in range(len(opponentEvidences)):
jointLaserInvisibility = inference.inferenceByVariableElimination(
net, ['laser', 'invisibility'], opponentEvidences[i], None)
strong_laser_prob = 0
weak_laser_prob = 0
invisible = 0
for assignmentDict in jointLaserInvisibility.getAllPossibleAssignmentDicts(
):
if assignmentDict['laser'] == 2:
strong_laser_prob += jointLaserInvisibility.getProbability(
assignmentDict)
if assignmentDict['laser'] == 1:
weak_laser_prob += jointLaserInvisibility.getProbability(
assignmentDict)
if assignmentDict['invisibility'] == 2 or assignmentDict[
'invisibility'] == 1:
invisible += jointLaserInvisibility.getProbability(
assignmentDict)
if i == 0:
if len(leftCapsules) < (capsuleLimit / 2):
if strong_laser_prob > weak_laser_prob:
x = random.randint(1, (width / 2) - 1)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
leftCapsules.append(ArmourCapsule(x, y))
if len(leftCapsules) < (capsuleLimit / 2):
if invisible > 0.5:
x = random.randint(1, (width / 2) - 1)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
leftCapsules.append(SonarCapsule(x, y))
while len(leftCapsules) < (capsuleLimit / 2):
x = random.randint(1, (width / 2) - 1)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
leftCapsules.append(GrenadeCapsule(x, y))
elif i == 1:
if len(rightCapsules) < (capsuleLimit / 2):
if strong_laser_prob > weak_laser_prob:
x = random.randint((width / 2), width - 2)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
rightCapsules.append(ArmourCapsule(x, y))
if len(rightCapsules) < (capsuleLimit / 2):
if invisible > 0.5:
x = random.randint((width / 2), width - 2)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
rightCapsules.append(SonarCapsule(x, y))
while len(rightCapsules) < (capsuleLimit / 2):
x = random.randint((width / 2), width - 2)
y = random.randint(1, height - 2)
if gameState.isValidPosition((x, y), self.isRed):
rightCapsules.append(GrenadeCapsule(x, y))
return leftCapsules + rightCapsules
def chooseCapsules(self, gameState, capsuleLimit, opponentEvidences):
# Do custom processing on the opponent's power evidence in order to
# effectively choose your capsules.
net = contestPowersBayesNet.powersBayesNet()
# for instance to calculate the joint distribution of the
# enemy agent 0 choosing invisibility and speed:
# from inference import inferenceByVariableElimination
jointSpeedInvisibility = inference.inferenceByVariableElimination(
net, ['invisibility', 'speed'], opponentEvidences[0], None)
# or compute the marginal factors of the enemy powers, given the
# evidenceAssignmentDict of the sum variables in the enemy powersBayesNet
enemyAgentMarginals = []
for evidence in opponentEvidences:
marginals = contestPowersBayesNet.computeMarginals(evidence)
enemyAgentMarginals.append(marginals)
# now perform other inference for other factors or use these marginals to
# choose your capsules
# these are not good choices, this is just to show you how to choose capsules
width, height = gameState.data.layout.width, gameState.data.layout.height
defenceCapsules = []
while len(defenceCapsules) < (capsuleLimit / 2):
if self.isRed:
x = width / 2 - 2
else:
x = width / 2 + 1
y = random.randint(1, height - 2)
if gameState.isValidPosition(
(x, y), self.isRed) and (x, y) not in [
c.getPosition for c in defenceCapsules
]:
if len(defenceCapsules) == 0:
defenceCapsules.append(SonarCapsule(x, y))
else:
defenceCapsules.append(GrenadeCapsule(x, y))
offenseCapsules = []
while len(offenseCapsules) < capsuleLimit / 2:
if self.isRed:
x = width / 2
else:
x = width / 2 - 1
y = random.randint(1, height - 2)
if gameState.isValidPosition(
(x, y), self.isRed) and (x, y) not in [
c.getPosition for c in offenseCapsules
]:
if len(offenseCapsules) == 0:
offenseCapsules.append(JuggernautCapsule(x, y))
else:
offenseCapsules.append(GrenadeCapsule(x, y))
return defenceCapsules + offenseCapsules