Untitled

from .OfficialAgent import BaselineAgent
import csv
import numpy as np

class MyAgent(BaselineAgent):
    def __init__(self, slowdown, condition, name, folder):
        super().__init__(slowdown, condition, name, folder)

        self.processedMessages = []

        def decide_on_actions(self, state, trustBeliefs, receivedMessages):

            for message in receivedMessages:
                 if message in self.processedMessages:
                     continue

                #robot checks the competence and willingness when doing certain tasks
                #if the competence/willingness is too low it will just do it alone but if it is above a threshold it will ask to work together

                #carrying a mildly injured victim can either do alone or working together
                #rescue a found mildly injured victim

                if self.message[-1] == 'Rescue together' and 'mild' in self._recentVic:

                    #check the comptence/willingness, below threshold then do it alone
                        if ((trustBeliefs[self._humanName]['competence'] + trustBeliefs[self._humanName]['willingness']) / 2 ) < 0.6:
                                    self._rescue = 'alone'
                                    self._answered = True
                                    self._waiting = False

                                    self._sendMessage(
                                        'Picking up ' + self._recentVic + ' in ' + self._door['room_name'] + '.',
                                        'RescueBot')

                    #above the threshold work together
                        else:
                                    self._rescue = 'together'
                                    self._answered = True
                                    self._waiting = False

                                    self._sendMessage('Lets carry ' + str(
                                        self._recentVic) + ' together! Please wait until I moved on top of ' + str(
                                        self._recentVic) + '.', 'RescueBot')

                objects = []

                #removing a small stone it can either do alone or working together
                for info in state.values():
                    if 'class_inheritance' in info and 'ObstacleObject' in info['class_inheritance'] and 'stone' in info['obj_id']:
                        objects.append(info)
                                    #remove the obstacle alone
                                    if ((trustBeliefs[self._humanName]['competence'] + trustBeliefs[self._humanName]['willingness']) / 2 ) < 0.6:
                                        self._rescue = 'alone'
                                        self._answered = True
                                        self._waiting = False

                                        self._sendMessage(
                                            'Removing stones blocking ' + str(self._door['room_name']) + '.',
                                            'RescueBot')

                                    #remove the obstacle together
                                    else:
                                        self._rescue = 'together'
                                        self._answered = True
                                        self._waiting = False

                                        self._sendMessage(
                                            'Lets remove stones blocking ' + str(self._door['room_name']) + '!',
                                            'RescueBot')

    # def _trustBelief(self, members, trustBeliefs, folder, receivedMessages):
    #     for message in receivedMessages:
    #         if message in self.processedMessages:
    #             continue
    #
    #         if 'Collect' in message:
    #             object_collected = message.split(":")[1].split(" in ")[0].strip()
    #
    #             if object_collected not in self._collectedVictims:
    #                 # Increase agent trust in a team member that rescued a victim
    #                 trustBeliefs[self._humanName]['competence']+=0.10
    #             else:
    #                 trustBeliefs[self._humanName]['competence']-=0.10
    #
    #             self.processedMessages.append(message)
    #
    #         if 'Search' in message:
    #             area = message.split()[-1]
    #
    #             if area not in self._searchedRooms:
    #                 # Increase agent trust in a team member that searched the room
    #                 trustBeliefs[self._humanName]['competence'] += 0.10
    #             else:
    #                 trustBeliefs[self._humanName]['competence'] -= 0.10
    #
    #             self.processedMessages.append(message)
    #
    #         if 'Found' in message:
    #             # Identify which victim and area it concerns
    #             if len(message.split()) == 6:
    #                 foundVic = ' '.join(message.split()[1:4])
    #             else:
    #                 foundVic = ' '.join(message.split()[1:5])
    #
    #             if foundVic in self._foundVictims:
    #                 # Increase agent trust in a team member if victims is in the drop zone
    #                 trustBeliefs[self._humanName]['competence'] += 0.10
    #             else:
    #                 trustBeliefs[self._humanName]['competence'] -= 0.10
    #
    #         if 'Remove' in message:
    #             area = message.split()[-1]
    #
    #             if area in self._searchedRooms:
    #                 trustBeliefs[self._humanName]['competence'] += 0.10
    #             else:
    #                 trustBeliefs[self._humanName]['competence'] -= 0.10
    #             self.processedMessages.append(message)
    #
    #             # Restrict the competence belief to a range of -1 to 1
    #             trustBeliefs[self._humanName]['competence'] = np.clip(trustBeliefs[self._humanName]['competence'], -1, 1)
    #             trustBeliefs[self._humanName]['willingness'] = np.clip(trustBeliefs[self._humanName]['willingness'], -1, 1)

        # Save current trust belief values so we can later use and retrieve them to add to a csv file with all the logged trust belief values
        with open(folder + '/beliefs/allTrustBeliefs.csv', mode='w') as csv_file:
            csv_writer = csv.writer(csv_file, delimiter=';', quotechar='"', quoting=csv.QUOTE_MINIMAL)
            csv_writer.writerow(['name','competence','willingness'])
            csv_writer.writerow([self._humanName,trustBeliefs[self._humanName]['competence'],trustBeliefs[self._humanName]['willingness']])

        print("Messages", receivedMessages)
        print("Members", members)
        print("Trust Beliefs",trustBeliefs)
        print("Distance", self._distanceHuman)
        print("Collected", self._collectedVictims)
        print("Found", self._foundVictims)