offensiveAgent_OffensiveReflexAgent.py

from captureAgents import CaptureAgent
import random, time, util
from game import Directions
import game
from capture import GameState
from util import nearestPoint
from ivar_off_reflex_agent import OffensiveReflexAgent
from ivar_offensive_agent import offensiveAgent
from mcts import Node
from mcts import MCTSAgent

#################
# Team creation #
#################

def createTeam(firstIndex, secondIndex, isRed,
               first = 'offensive_ReflexAgent', second = 'play_offensiveAgent'): 
    return [eval(first)(firstIndex), eval(second)(secondIndex)]

##########
# Agents #
##########

class offensive_ReflexAgent(OffensiveReflexAgent):
  """
  A base class for reflex agents that chooses score-maximizing actions
  """
 
  def registerInitialState(self, gameState):
    self.start = gameState.getAgentPosition(self.index)
    CaptureAgent.registerInitialState(self, gameState)

  def chooseAction(self, gameState):
    """
    Picks among the actions with the highest Q(s,a).
    """
    gameState = GameState.deepCopy(self=gameState)
    best_action =  OffensiveReflexAgent.chooseAction(self, gameState)
    return best_action

class play_offensiveAgent(offensiveAgent):
  """
  A Dummy agent to serve as an example of the necessary agent structure.
  You should look at baselineTeam.py for more details about how to
  create an agent as this is the bare minimum.
  """
    
  def registerInitialState(self, gameState):
    CaptureAgent.registerInitialState(self, gameState)

  def chooseAction(self, gameState):
    """
    Picks among the actions with the highest Q(s,a).
    """
    gameState = GameState.deepCopy(self=gameState)
    best_action = offensiveAgent.chooseAction(self, gameState)
    return best_action