def chooseAction(self, gameState):
self.updateInference(gameState)
minimaxMod = MinimaxModule(self)
minimaxMod.setImpatience(0.1)
minimaxVals = minimaxMod.getMinimaxValues(gameState, self.index,
self.isRed, 0.8)
bestActions = []
bestVal = 0
for pair in minimaxVals:
if (bestVal < pair[1]):
bestActions = []
if (len(bestActions) == 0 or (bestVal == pair[1])):
bestActions.append(pair[0])
bestVal = pair[1]
if (len(bestActions) == 0):
return gameState.getLegalActions(self.index)[0]
return random.choice(bestActions)
def chooseAction(self, gameState):
print("Agent " + str(self.index) + " choosing an action")
minimaxMod = MinimaxModule(self)
minimaxMod.setImpatience(
float(self.heuristicWeights['attackModule_percentImpatience']) /
100.0)
minimaxVals = minimaxMod.getMinimaxValues(gameState, self.index,
self.isRed, 0.1)
bestActions = []
bestVal = 0
for pair in minimaxVals:
if (bestVal < pair[1]):
bestActions = []
if (len(bestActions) == 0 or (bestVal == pair[1])):
bestActions.append(pair[0])
bestVal = pair[1]
if (len(bestActions) == 0):
return gameState.getLegalActions(self.index)[0]
return random.choice(bestActions)
