ghostAgents.py 文件源码

 复制代码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.scaredTimer > 0

        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 = [manhattanDistance( pos, pacmanPosition ) for pos in newPositions]
        if isScared:
            bestScore = max( distancesToPacman )
            bestProb = self.prob_scaredFlee
        else:
            bestScore = min( distancesToPacman )
            bestProb = self.prob_attack
        bestActions = [action for action, distance in zip( legalActions, distancesToPacman ) if distance == bestScore]

        # Construct distribution
        dist = util.Counter()
        for a in bestActions: dist[a] = bestProb / len(bestActions)
        for a in legalActions: dist[a] += ( 1-bestProb ) / len(legalActions)
        dist.normalize()
        return dist