Source Code for Module teamwork.agent.MemoryAgent

 1  from teamwork.agent.RecursiveAgent import RecursiveAgent 
 2  from copy import deepcopy 
 3   
 4 -class MemoryAgent(RecursiveAgent): 
 5      ''' 
 6      Memory is stored in a list such that the most recent memory is the 0th element in the list 
 7      and the oldest memory is the n-1th memory in the list where n is the memory length 
 8      ''' 
 9       
10 -    def __init__(self,name=''): 
11          RecursiveAgent.__init__(self,name) 
12          self.memoryLength = 3 
13          self.memory = [] 
14   
15 -    def updateMemory(self, actions, previousBeliefs): 
16          memory = {} 
17   
18          #update the memory of the action taken 
19          memory['actions'] = actions.copy() 
20   
21          #update beliefs 
22          memory['previousBeliefs'] = deepcopy(previousBeliefs) 
23   
24          #insert the memory 
25          self.memory.insert(0, memory) 
26   
27          #make sure we don't go over the memory length 
28          if len(self.memory) > self.memoryLength: 
29              self.memory.pop() 
30              
31  if __name__ == '__main__': 
32      from teamwork.multiagent.GenericSociety import GenericSociety 
33      from teamwork.multiagent.sequential import SequentialAgents 
34      import teamwork.examples.school.SchoolClasses as classModule 
35      from teamwork.multiagent.Historical import HistoricalAgents 
36   
37      #We need to get a scenario 
38      society = GenericSociety() 
39      society.importDict(classModule.classHierarchy) 
40   
41      #Instantiate the agents  
42      victim = society.instantiate("Victim", "Victim") 
43      onlooker = society.instantiate("Onlooker", "Onlooker") 
44      bully = society.instantiate("Bully", "Bully") 
45      teacher = society.instantiate("Teacher", "Teacher") 
46       
47      #Set up the relationships 
48      victim.relationships['victim'] = ['Victim'] 
49      onlooker.relationships['victim'] = ['Victim'] 
50      bully.relationships['victim'] = ['Victim'] 
51   
52      #Instantiate the scenario 
53      entities = [victim, onlooker, bully, teacher] 
54      agents = SequentialAgents(entities) 
55      agents.applyDefaults() 
56      agents.compileDynamics() 
57   
58      result = agents.microstep() 
59      agents.microstep() 
60   
61      print "\n\nmemory!\n\n" 
62  #    print bully.memory[0]['previousBeliefs']['state'].items()[0][0].keys()[1]['entity'] 
63  #    print bully.memory[0]['previousBeliefs']['state'].items()[0][0].keys() 
64      print victim.entities.getStateKeys().keys() 
65   
66  #    for agent in agents.activeMembers(): 
67  #        print agent.name 
68  #        for mem in agent.memory: 
69  #            print "Previous Beliefs:" 
70  #            for belkey in mem['previousBeliefs'].keys(): 
71  #                if belkey == 'state': 
72  #                    print mem['previousBeliefs'][belkey].keys()[0] 
73  #            print "\n" 
74  # 
75  #        print "\n\n" 
76