focus.set("goal:pizza object:dough")
def dough(focus="goal:pizza object:dough"): # if focus buffer has this chunk then....
print "I have made a round piece of dough" # print
focus.set("goal:pizza object:cheese") # change chunk in focus buffer
def cheese(focus="goal:pizza object:cheese"): # the rest of the productions are the same
print "I have put cheese on the dough" # but carry out different actions
focus.set("goal:pizza object:ham")
def chicken(focus="goal:pizza object:ham"):
print "I have put chicken on the cheese"
focus.set("goal:pizza object:sauce")
def sauce(focus="goal:pizza object:cheese"):
print "I have put sauce on the chicken"
print "I have made a chicken and cheese pizza"
focus.set("goal:stop")
def stop_production(focus="goal:stop"):
self.stop() # stop the agent
tim = MyAgent() # name the agent
pizzashop = MyEnvironment() # name the environment
pizzashop.agent = tim # put the agent in the environment
ccm.log_everything(pizzashop) # print out what happens in the environment
pizzashop.run() # run the environment
ccm.finished() # stop the environment
focus.set('new_trial')
def no_prime(focus='prime'): #use counter
print "reveal the problem"
motor.reveal_operator()
motor.reveal_numbers()
focus.set('new_trial')
def numbers_prime(focus='prime'): #use counter
print "reveal the numbers"
motor.reveal_numbers()
focus.set('operator_late')
def operator_late(focus='operator_late', numbers='visible:yes', operator='visible:no'):
print "complete the problem with the operator"
motor.reveal_operator()
focus.set('new_trial')
Ppt=Participant()
Experimenter=Referee()
env=Arithmetic()
env.agent1=Ppt
env.agent2=Experimenter
#ccm.log_everything(env)
env.run(4)
ccm.finished()
b_focus.set('change_state')
motor.motor_finst_reset()
print 'I have exposed ', target
def cut_wire(b_method='method:cut_wire target:?target state:running',
b_focus='change_state'): # target is the chunk to be altered
motor.change_state(target, "cut")
b_method.set('method:change_state target:?target state:running')
b_operator.set('operator:cut target:?target state:running')
b_focus.set('cutting_wire')
print 'cut wire'
print 'target object = ', target
def wire_cut(b_method='method:?method target:?target state:running',
motor_finst='state:finished',
b_focus='cutting_wire'):
b_method.set('method:?method target:?target state:finished')
motor.motor_finst_reset()
b_focus.set('wire_is_cut')
print 'I have cut ', target
############## run model #############
tim = MyAgent() # name the agent
subway = MyEnvironment() # name the environment
subway.agent = tim # put the agent in the environment
ccm.log_everything(subway) # print out what happens in the environment
subway.run() # run the environment
ccm.finished() # stop the environment
def Problem(focus='no coffee filters'):
print "No coffee filters ... what is the best subsitute filter?"
print "I'm search for knowledge ..."
DM.request('substitute_filter:?') # KNOWLEDGE REQUEST
focus.set('next')
def Remember(focus='next',
DMbuffer='substitute_filter:?substitute_filter'):
print " "
print "I recall a good substitute filter is a ..."
print substitute_filter
# here there is no "focus.set" - the next production fires off the retrieved knowledge chunk (above) which then triggers the production below.
def Finished(
focus='strainer used'
): # this is cued by production above tited "Fires_Off_Knowledge_Chunk" (above)
print " " # this demonstrates how knowledge serves as a buffer condition that triggers the next productions
motor.finish_coffee()
print "The coffee is finished."
self.stop()
Julian = MyAgent()
env = MyEnvironment()
env.agent = Julian
# ccm.log_everything(env)
env.run()
ccm.finished()
def shutdown(self) -> str:
ccm.finished()
return "The result of CmuActrModel:shutdown()"
