We abstract away from syntactic parsing, among other things.
"""
import pyactr as actr
actr.chunktype("word", "meaning, category, number, synfunction")
actr.chunktype("goal_lexeme", "task, category, number")
carLexeme = actr.makechunk(nameofchunk="car",
typename="word",
meaning="[[car]]",
category="noun",
number="sg",
synfunction="subject")
agreement = actr.ACTRModel()
dm = agreement.decmem
dm.add(carLexeme)
agreement.goal.add(
actr.chunkstring(string="""
isa goal_lexeme
task agree
category verb"""))
agreement.productionstring(name="retrieve",
string="""
=g>
isa goal_lexeme
category verb
"""
A simple top-down parser.
"""
import pyactr as actr
environment = actr.Environment(focus_position=(320, 180))
actr.chunktype("read", "state word goal_cat")
actr.chunktype("parsing", "top bottom")
actr.chunktype("word", "form cat")
parser = actr.ACTRModel(environment)
parser.decmem.add(
actr.chunkstring(string="isa word form 'Mary' cat 'ProperN'"))
parser.decmem.add(
actr.chunkstring(string="isa word form 'Bill' cat 'ProperN'"))
parser.decmem.add(actr.chunkstring(string="isa word form 'likes' cat 'V'"))
parser.goal.add(
actr.chunkstring(string="""
isa read
state start
goal_cat 'S'"""))
parser.goal = "g2"
parser.goals["g2"].add(
actr.chunkstring(string="""
isa parsing
top 'S'"""))
parser.goals["g2"].delay = 0.2
return np.arange(start=-time_interval, stop=-(time_interval*word_freq)-1, step=-time_interval)
else:
return np.array([0])
def calculate_activation(parser, freq_array):
"""
Calculate activation using parser and freq_array.
"""
return np.log(np.sum(freq_array ** (-parser.model_parameters["decay"])))
sentences_csv = load_file(SENTENCES, sep=",") #sentences with frequencies
environment = actr.Environment(focus_position=(320, 180))
parser = actr.ACTRModel(environment, subsymbolic=True, retrieval_threshold=-20,
decay = 0.5, latency_factor=0.04, latency_exponent=0.08,
eye_mvt_angle_parameter=2000, emma_noise=False,
rule_firing=0.05, motor_prepared=True, automatic_visual_search=False)
temp_dm = {}
temp_activations = {}
words = sentences_csv.groupby('word', sort=False)
actr.chunktype("word", "form cat")
actr.chunktype("parsing_goal", "task")
actr.chunktype("reading", "state position word reanalysis retrieve_wh what_retrieve tag")
actr.chunktype("action_chunk", "ACTION ACTION_RESULT_LABEL ACTION_PREV WORD_NEXT0_LEX WORD_NEXT0_POS TREE0_LABEL TREE1_LABEL TREE2_LABEL TREE3_LABEL TREE0_HEAD TREE0_HEADPOS TREE0_LEFTCHILD TREE0_RIGHTCHILD TREE1_HEAD TREE1_HEADPOS TREE1_LEFTCHILD TREE1_RIGHTCHILD TREE2_HEAD TREE2_HEADPOS TREE3_HEAD ANTECEDENT_CARRIED")
"""
A basic model of grammar.
"""
import pyactr as actr
regular_grammar = actr.ACTRModel()
actr.chunktype("goal_chunk", "mother daughter1 daughter2 state")
dm = regular_grammar.decmem
regular_grammar.goal.add(
actr.chunkstring(string="""
isa goal_chunk
mother NP
state rule
"""))
regular_grammar.productionstring(name="NP ==> N NP",
string="""
=g>
isa goal_chunk
mother NP
daughter1 None
daughter2 None
state rule
==>
=g>
isa goal_chunk
daughter1 N
def __init__(self, env, **kwargs):
self.m = actr.ACTRModel(environment=env, **kwargs)
actr.chunktype("pair", "probe answer")
actr.chunktype("goal", "state, arg1, arg2, sum, end")
self.dm = self.m.decmem
self.start = actr.makechunk(nameofchunk="start", typename="chunk", value="start")
actr.makechunk(nameofchunk="done", typename="chunk", value="done")
self.m.set_goal("g2")
self.m.goals["g2"].delay=0.2
self.m.productionstring(name="find_probe", string="""
=g>
isa goal
state start
?visual_location>
buffer empty
==>
=g>
isa goal
state attending
?visual_location>
attended False
+visual_location>
isa _visuallocation
value B
screen_x lowest
screen_y closest""") #this rule is used if automatic visual search does not put anything in the buffer
self.m.productionstring(name="move_in_line", string="""
=g>
isa goal
state attending
?visual_location>
state error
==>
=g>
isa goal
state attending
?visual_location>
attended False
+visual_location>
isa _visuallocation
value B
screen_x lowest
screen_y closest""", utility=20) #this rule is used if automatic visual search does not put anything in the buffer
self.m.productionstring(name="check_probe", string="""
=g>
isa goal
state start
?visual_location>
buffer full
==>
=g>
isa goal
state attending""") #this rule is used if automatic visual search is enabled and it puts something in the buffer
self.m.productionstring(name="attend_probe", string="""
=g>
isa goal
state attending
=visual_location>
isa _visuallocation
screen_x ~None
?visual>
state free
==>
=g>
isa goal
state reading
+visual>
isa _visual
cmd move_attention
screen_pos =visual_location""")
self.m.productionstring(name="encode_probe", string="""
=g>
isa goal
state reading
=visual>
isa _visual
value =val
==>
=g>
isa goal
sum None
state None""")
self.m.productionstring(name="retrieve_addition", string="""
=g>
isa add
state None
arg1 =num1
arg2 =num2
arg2 ~None
sum None
?retrieval>
state free
buffer empty
==>
=g>
isa add
state None
+retrieval>
isa add
arg1 =num1
arg2 =num2""", utility=7)
self.m.productionstring(name="terminate_addition", string="""
=g>
isa add
=retrieval>
isa add
arg1 ~None
sum =v7
==>
~retrieval>
=g>
isa add
state move
sum =v7""", utility=7)
for i, nums in enumerate([(2, 2), (4, 4), (4, 2), (2, 4)]):
self.m.productionstring(name="retrieve_addition_terminate_addition" + str(i), string="""
=g>
isa add
state None
arg1 """+str(nums[0])+"""
arg2 """+str(nums[1])+"""
sum None
?retrieval>
state free
buffer empty
==>
=g>
isa add
state move
sum """+str(nums[0]+nums[1]), utility=7)
self.m.productionstring(name="retrieve failure", string="""
=g>
isa goal
state None
arg2 ~None
?retrieval>
state error
==>
=g>
isa goal
state None
arg2 None""")
for i in range(10):
self.m.productionstring(name="fast_increment" + str(i), string="""
=g>
isa goal
state None
arg1 """+str(i)+"""
sum None
?retrieval>
state free
buffer empty
==>
=g>
isa goal
state move
sum """+str(i+1), utility=6)
self.m.productionstring(name="retrieve count", string="""
=g>
isa goal
state None
arg1 =x
sum None
?retrieval>
state free
buffer empty
==>
+retrieval>
isa add
arg1 =x
arg2 1""", utility=4)
self.m.productionstring(name="increment", string="""
=g>
isa goal
state None
=retrieval>
isa add
arg2 1
sum =y
sum ~None
==>
~retrieval>
=g>
isa goal
state move
sum =y""")
self.m.productionstring(name="move_vis_loc", string="""
=g>
isa goal
state move
sum =csum
sum ~None
=visual_location>
isa _visuallocation
screen_y =sy
==>
=g>
isa goal
state attending
arg2 None
arg1 =csum
~visual>
?visual_location>
attended False
+visual_location>
isa _visuallocation
value B
screen_x closest
screen_y =sy""")
self.m.productionstring(name="can_find", string="""
=g>
isa goal
sum =x
end =x
?manual>
state free
==>
~retrieval>
~g>
+manual>
isa _manual
cmd press_key
key 'J'""", utility=5)
self.m.productionstring(name="cannot_find", string="""
=g>
isa goal
state attending
?visual_location>
state error
?manual>
state free
==>
~retrieval>
~g>
+manual>
isa _manual
cmd press_key
key 'F'""", utility=-5)
self.productions = self.m._ACTRModel__productions
import pyactr.utilities as utilities
import string
import warnings
DECAY = 0.5
#MP = 1.3
#RT = 2.8
SIMULATIONNUMBER = int(sys.argv[1])
MP = 2.0
RT = 4
ADDITION = str(SIMULATIONNUMBER) + str(MP) + str(RT)
addition = actr.ACTRModel(subsymbolic=True, retrieval_threshold=-2.25, latency_factor=0.1, latency_exponent=0.5, instantaneous_noise = 0.25, decay=DECAY, buffer_spreading_activation={"g": 1}, strength_of_association=3.3, association_only_from_chunks=False)
actr.chunktype("countOrder", ("first", "second"))
actr.chunktype("number", "value")
actr.chunktype("add", ("state", "arg1", "arg2", "sum"))
dm = addition.decmem
numbers = []
for i in range(0, 20):
#numbers.append(actr.makechunk("number"+str(i), "number", value=i))
numbers.append(str(i))