minimal ai scores -10 on average

minimalAI.py

from Agent import Agent
from collections import deque
from enum import Enum

class MyAI ( Agent ):
    
    class Action (Enum):
        
        CHECK_FOR_GOLD = 1
    
    def __init__ ( self ):
        self.actionList = deque( [] )
        self.perceptArray = []
     
       

    def continueActionSequence( self, glitter ):
        action = self.actionList.popleft()
        if action == self.Action.CHECK_FOR_GOLD:
            self.check_gold(glitter)
            action = self.actionList.popleft()
        
        return action

    def check_gold(self,glitter):
        if glitter:
            self.actionList.appendleft(Agent.Action.GRAB)

    def minimalAction( self ):
        self.actionList.append( Agent.Action.FORWARD )
        
        self.actionList.append( self.Action.CHECK_FOR_GOLD )
        self.turn_around()
        self.actionList.append( Agent.Action.FORWARD )
        # back in start tile
        self.actionList.append( Agent.Action.TURN_RIGHT )
        self.actionList.append( Agent.Action.FORWARD )
        self.actionList.append( self.Action.CHECK_FOR_GOLD )
        self.turn_around()
        self.actionList.append( Agent.Action.FORWARD )
        # back in start tile
        self.exit_world()
        return self.actionList.popleft()

    def turn_around(self):
        self.actionList.append( Agent.Action.TURN_LEFT )
        self.actionList.append( Agent.Action.TURN_LEFT )

    def kill_wumpus(self):
        self.actionList.append(Agent.Action.SHOOT)
        self.exit_world()
    
    def exit_world(self):
        
        self.actionList.append(Agent.Action.CLIMB)

    def getAction( self, stench, breeze, glitter, bump, scream ):
        if  len( self.actionList ) > 0 :
            return self.continueActionSequence(glitter)
        else :
            if stench: 
                self.kill_wumpus()
                return self.actionList.popleft()
            
            elif breeze:
                self.exit_world()
                return self.actionList.popleft()
            
            else:
                
                # explore two adjacent squares
                return self.minimalAction()

'''
if actionSequence
    return actionSequence.pop()
else:
    Generate Action Sequence based on current knowledge/belief


Strategy:
Agent builds
Agent "explores" unvisited rooms (tile X,Y that agent is currently in but has not visited before).
     Exploring a room changes current knowledge/belief state.
'''