Linear Combination Heuristic

LinearCombinationHeuristic.py

class LinearCombinationHeuristic:
  def __init__(self, game, role, weights, MAX_POSSIBLE_ACTIONS, MAX_POSSIBLE_STATES):
    self.game = game
    self.role = role
    self.weights = weights
    self.MAX_POSSIBLE_ACTIONS = MAX_POSSIBLE_ACTIONS
    self.MAX_POSSIBLE_STATES = MAX_POSSIBLE_STATES
    self.heuristics = [actionMobility, stateMobility, actionFocus, stateFocus, goalValue]
    assert(len(self.heuristics) == len(self.weights))
  
  def evaluate(self, state):
    return sum(self.weights[i] * self.heuristics[i](state) for i in xrange(len(self.heuristics)))
      
  def actionMobility(self, state):
    return (self.game.getLegalMoves(state, self.role) * 100.0) / self.MAX_POSSIBLE_ACTIONS
    
  def stateMobility(self, state):
    return (len({self.game.getNextState(state, jointMove) for jointMove in self.game.getLegalJointMoves(state)}) * 100.0) / self.MAX_POSSIBLE_STATES
    
  def actionFocus(self, state):
    # There's no need to recompute action mobility. This code is just for illustration.
    return 100.0 - actionMobility(state)
    
  def stateFocus(self, state):
    # There's no need to recompute state mobility. This code is just for illustration.
    return 100.0 - stateMobility(state)
    
  def goalValue(self, state):
    return self.game.getGoalValues(state)[self.role]