betterEvaluationFunction

def betterEvaluationFunction(currentGameState):
    """
    Your extreme ghost-hunting, pellet-nabbing, food-gobbling, unstoppable
    evaluation function (question 5).

    DESCRIPTION:
        This is essentially our reflex agent, but pertaining the current state only.
        1.  Start with score 0
        2.  Add 200 * (4 - # of capsules left)
            This incites pacman to eat capsules (if there are <4; qty can be varied arbitrarily)
        3.  Subtract twice the distance to the nearest capsule (if pacman is w/in 5 of it)
            This makes pacman beeline for a capsule once he gets close
        4.  Subtract the distance to the nearest piece of food (if NOT w/in 5 of a capsule)
            This makes pacman continuously move toward food
        5.  Subtract the distance to the nearest ghost if it is "afraid"
            This makes pacman try to eat vulnerable ghosts
        6.  Add the distance to the nearest "non-afraid" ghost (if pacman is w/in 3 of it)
            This makes pacman keep away from ghosts, but also not give undue thought to distant ghosts
        7.  Add 4 (if NOT w/in 3 of any ghost)
            This keeps pacman from trying to be too friendly with the ghosts :)
        8.  Subtract 500 if pacman occupies the same space as a ghost
            Prevents pacman from suiciding
        9.  Subtract 250 if pacman occupies a space adjacent to a ghost
            Keeps pacman from getting into the ghosts' attack range
        10. Subtract the amount of food left on the board
            Gives pacman an incentive to eat food he is adjacent to
        11. Add 4 times the current score
            Clobbers any corner cases where pacman gets stuck next to a piece of food
    """
    newPos = currentGameState.getPacmanPosition()
    newFood = currentGameState.getFood()
    newGhostStates = currentGameState.getGhostStates()
    newScaredTimes = [ghostState.scaredTimer for ghostState in newGhostStates]
    newGhostPositions = [ghostState.getPosition() for ghostState in newGhostStates]
    newFoodCount = newFood.count()
    newFoodPositions = newFood.asList()
    newCapsulePositions = currentGameState.getCapsules()

    scaredGhosts = []
    numGhosts = len(newGhostStates)
    for i in xrange(0, numGhosts):
        if not newScaredTimes[i] == 0:
            scaredGhosts.append(newGhostPositions[i])

    score = 0

    targetCapsule = None
    capsuleDist = 999999
    for capsulePos in newCapsulePositions:
        tempDist = manhattanDistance(newPos, capsulePos)
        if tempDist < 5:
            targetCapsule = capsulePos
            capsuleDist = tempDist
    if not targetCapsule == None:
        score -= capsuleDist * 2
    score += 200 * (4 - len(newCapsulePositions))

    minDist = 999999
    bestFood = None
    if capsuleDist >= 5:
        for foodPos in newFoodPositions:
            currDist = manhattanDistance(newPos, foodPos)
            if currDist < minDist:
                minDist = currDist
                bestFood = foodPos
        if not newFoodCount == 0:
            score -= minDist

    minDist = 999999
    isOnGhost = False
    isNextToGhost = False
    closestGhost = None
    for ghostPos in newGhostPositions:
        currDist = manhattanDistance(newPos, ghostPos)
        if currDist == 0 and ghostPos not in scaredGhosts:
            isOnGhost = True
        if currDist == 1 and ghostPos not in scaredGhosts:
            isNextToGhost = True
        if currDist < minDist:
            minDist = currDist
            closestGhost = ghostPos
    if closestGhost in scaredGhosts:
        score -= minDist
    else:
        if minDist < 3:
            score += minDist
        else:
            score += 4

    score -= newFoodCount

    if isOnGhost:
        score -= 500
    if isNextToGhost:
        score -= 250

    score += currentGameState.getScore() * 4

    return score