lexical decision model

lex_dec_model.py

words = [{1: {'text': 'elephant', 'position': (320, 180)}},
        {2: {'text': 'wug', 'position': (220, 140)}},
        {3: {'text': 'dog', 'position': (320, 180)}}]

import pyactr as actr

environment = actr.Environment(focus_position=(0,0))
lex_decision = actr.ACTRModel(
    environment=environment,
    automatic_visual_search=False,
    motor_prepared=True
)

actr.chunktype("goal", "state")
actr.chunktype("word", "form")

dm = lex_decision.decmem

for string in {"elephant", "dog", "crocodile"}:
    dm.add(actr.makechunk(typename="word", form=string))

g = lex_decision.goal

g.add(actr.makechunk(nameofchunk="beginning",
                     typename="goal",
                     state="start"))

lex_decision.productionstring(name="find word", string="""
    =g>
    isa     goal
    state   start
    ?visual_location>
    buffer  empty
    ==>
    =g>
    isa     goal
    state   attend
    +visual_location>
    isa _visuallocation
    screen_x closest
""")

lex_decision.productionstring(name="attend word", string="""
    =g>
    isa     goal
    state   attend
    =visual_location>
    isa    _visuallocation
    ?visual>
    state   free
    ==>
    =g>
    isa     goal
    state   retrieving
    +visual>
    isa     _visual
    cmd     move_attention
    screen_pos =visual_location
    ~visual_location>
""")

lex_decision.productionstring(name="retrieving", string="""
    =g>
    isa     goal
    state   retrieving
    =visual>
    isa     _visual
    value   =val
    ==>
    =g>
    isa     goal
    state   retrieval_done
    +retrieval>
    isa     word
    form    =val
""")

lex_decision.productionstring(name="lexeme retrieved", string="""
    =g>
    isa     goal
    state   retrieval_done
    ?retrieval>
    buffer  full
    state   free
    ==>
    =g>
    isa     goal
    state   waiting
    +manual>
    isa     _manual
    cmd     press_key
    key     J
""")

lex_decision.productionstring(name="no lexeme found", string="""
    =g>
    isa     goal
    state   retrieval_done
    ?retrieval>
    buffer  empty
    state   error
    ==>
    =g>
    isa     goal
    state   waiting
    +manual>
    isa     _manual
    cmd     press_key
    key     F
""");

lex_decision.productionstring(name="button finished", string="""
    =g>
    isa     goal
    state   waiting
    ?manual>
    state  free
    ==>
    =g>
    isa     goal
    state   start
""");

lex_dec_sim = lex_decision.simulation(
    realtime=False,
    gui=False,
    environment_process=environment.environment_process,
    stimuli=words,
    triggers=['J','F'],
    times=1)

lex_dec_sim.run(max_time=3)
# produces error "ACTRError: In environment, stimuli must be the same length as triggers or one of the two must be of length 1"