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#!/usr/bin/env python3
import pyactr as actr
from pprint import pprint
from model_init import init
import prod_addition
import prod_subtraction
import prod_comp
import prod_multi
import prod_numbers
import prod_procedure
import prod_motor
import prod_vis
import model_env
def add_goal(goal, op, arg1, arg2):
goal.add(actr.makechunk("", "math_goal", op=op, task=op, arg1=arg1, arg2=arg2))
def wait_input():
op = input("op\n")
arg1 = input("arg1\n")
arg2 = input("arg2\n")
return op, int(arg1), int(arg2)
def add_proc(goal, proc):
# input()
goal.add(actr.makechunk("", "math_goal", proc=proc, ones_carry=""))
def start():
condition = "fixed"
training_N = 1
test_N = 1
stimuli = model_env.Stimuli(condition, training_N=training_N, test_N=test_N)
pprint(stimuli.training_order)
pprint(stimuli.test_order)
stimuli.generate_stimuli()
pprint(stimuli.training_stimuli)
pprint(stimuli.test_stimuli)
stimulus = stimuli.next_stimulus()
# op, arg1, arg2 = wait_input()
Model, DM, goal, imaginal, env = init()
# Model.model_parameters["subsymbolic"] = True
# Model.model_parameters["partial_matching"] = True
Model.model_parameters["activation_trace"] = True
Model.model_parameters["instantaneous_noise"] = .2
Model.model_parameters["utility_alpha"] = 0.5
Model.model_parameters["utility_noise"] = 0.5
Model.model_parameters["production_compilation"] = True
Model.model_parameters["utility_learning"] = True
# add_goal(goal, op, arg1, arg2)
add_proc(goal, "next_proc")
prod_procedure.procedures(Model)
number_prods = prod_numbers.number(Model)
add_prods = prod_addition.addition(Model)
sub_prods = prod_subtraction.subtraction(Model)
greater_prods = prod_comp.greater_than(Model)
less_prods = prod_comp.lesser_than(Model)
multi_prods = prod_multi.multiplication(Model)
motor_prods = prod_motor.procedures(Model)
visual_prods = prod_vis.procedures(Model)
for p in Model.productions:
Model.productions[p].__setitem__("utility", 1)
print("goal: ", goal)
# print("imaginal: ", imaginal)
sim = Model.simulation(
gui=False,
environment_process=env.environment_process,
stimuli=stimulus,
realtime=False,
# triggers="space",
triggers="b",
)
# pprint(sim._Simulation__pr.rules)
# pprint(sim._Simulation__pr.ordered_rulenames)
i = 1
j = 1
phase = "training"
userinput = {"training": {}, "test": {}}
while True:
if j > training_N:
phase = "test"
sim.step()
# print(goal)
if sim.current_event.time >= 900:
pprint(sim.current_event)
break
if "KEY PRESSED" in sim.current_event.action:
if not stimuli.current_stimulus_id in userinput[phase]:
userinput[phase][stimuli.current_stimulus_id] = {}
if not str(i) in userinput[phase][stimuli.current_stimulus_id]:
userinput[phase][stimuli.current_stimulus_id][str(i)] = []
userinput[phase][stimuli.current_stimulus_id][str(i)].append(
sim.current_event.action.split(":")[1].strip()
)
if "RULE FIRED:" in sim.current_event.action and " and " in sim.current_event.action:
print("FIRED COMPILED RULE!!!!")
print(Model.productions[sim.current_event.action[12:]])
# break
if sim.current_event.action == "NO RULE FOUND":
print(goal)
if sim.current_event.action == "KEY PRESSED: SPACE":
sim._Simulation__env.stimulus = stimuli.update_current_stimulus(
f"Answer{i}",
int("".join(userinput[phase][stimuli.current_stimulus_id][str(i)][:-1])),
)
i += 1
pprint(userinput)
pprint("NEW PROC")
if i <= 6:
goal.add(
actr.makechunk("", "math_goal", proc="next_proc", ones_carry="")
)
elif i >= 7 and j < training_N+test_N:
print("Stimulus Done, next stimulus")
sim._Simulation__env.stimulus = stimuli.next_stimulus()
goal.add(
actr.makechunk("", "math_goal", proc="next_proc", ones_carry="")
)
i = 1
j += 1
elif i >= 7 and j >= training_N+test_N:
print("DONE")
break
# sim.run(max_time=25)
print("training order: ", stimuli.training_order_list)
print("test order: ", stimuli.test_order_list)
pprint(userinput)
print("Simulation time: ", sim.show_time())
print("goal: ", goal)
print(sim.current_event)
# pprint(vars(sim))
pprint(vars(sim._Simulation__env))
# print(sim.__env)
# sim.__printenv__()
# print(envs.stimulus)
# print("imaginal: ", imaginal)
math_goals = [sim for sim in list(DM) if sim.typename == "procedure"]
# print(math_goals)
# pprint(Model.productions)
# for p in Model.productions:
# print(p)
# print(Model.productions[p])#.__setitem__("utility", 1)
# print("\n")
# print("#######used prods########")
# print(sim.ordered_rulenames)
pprint(sim._Simulation__pr.rules)
pprint(sim._Simulation__pr.ordered_rulenames)
if __name__ == "__main__":
start()
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