Transcript Cognitive Psychology (CPsy)

Integrating Object-Oriented Technology
with
Cognitive Modeling
Pamela E. Scott-Johnson, Ph.D.
Department of Psychology, College of Liberal Arts
Bheem Kattel, Ph.D., CPE
Industrial, Manufacturing, & Information Engineering, School of Engineering
LeeRoy Bronner, Ph.D., P.E.
Industrial, Manufacturing, & Information Engineering, School of Engineering
Cognitive Models
• Anderson & Byrne
o Carnegie Melon
University
o Currently used by
HRED (Army)
• Overview of ACT-R
• Experiments
o Face / Pattern
Recognitions
o Terrains
o Eye Tracking
• Object Orienting
ACT-R
• A cognitive architecture: a theory about how human
cognition works.
• Looks like a programming language.
o
Its constructs reflect assumptions about human
cognition. These assumptions are based on numerous
facts derived from psychology experiments.
• These assumptions can be tested by comparing the
results of the model with the results of people doing
the same tasks.
• By "results" we mean the traditional measures of
cognitive psychology:
o
o
o
time to perform the task,
accuracy in the task, and,
(more recently) neurological data such as those
obtained from FMRI.
Motivations for a Cognitive
Architecture
• Philosophy: Provide a unified understanding of the
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•
•
•
•
mind.
Psychology: Account for experimental data.
Education: Provide cognitive models for intelligent
tutoring systems and other learning environments.
Human Computer Interaction: Evaluate artifacts
and help in their design.
Computer Generated Forces: Provide cognitive
agents to inhabit training environments and games.
Neuroscience: Provide a framework for interpreting
data from brain imaging.
Anderson & Byrne Tutorial
Approach: Integrated Cognitive
Models
• Cognitive model = computational process
that thinks/acts like a person
• Integrated cognitive models…
Driver
Model
User
Model
User
Model
•••
These Goals for Cognitive
Architectures Require
• Integration, not just of different aspects of
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higher level cognition but of cognition,
perception, and action.
Systems that run in real time.
Robust behavior in the face of error, the
unexpected, and the unknown.
Parameter-free predictions of behavior.
Learning.
Atomic Components of Thought (ACT-R)
• ACT-R is a production system theory that tries to explain human.
Cognition through a model of knowledge structures.
• Two types of knowledge declarative and procedural.
• Declarative knowledge.
• Corresponds to things we know and can describe.
• Represented by structures call chunks.
• Chunk defined by a: type and slots ( ES –frame).
• Example: dog chased the cat – type: chase, agent: dog, object: cat.
• Procedural knowledge.
• Knowledge displayed by our behavior but we are not conscious of.
• No one can describe the rules by which we speak a language, but
we do.
• Defined by production rules:
• Example: IF the goal is to classify a person and he is unmarried.
Then classify him as a bachelor (action part).
• Chunks and productions are the basic building blocks of ACT-R.
ETA
Embodied Cognition Task Artefact Triad
Embodied Cognition
Interactive Behavior
Task
Artefact
The user’s ability
to interact with an interface is dependent upon the properties of the
Figure 1. The embodied cognition – task-artefact triad. Adapted from
1.
Byrne 2001 article.
The embodied
cognition or cognitive, perceptual, and motor capacities of the user,
2.
The task(s) that the user is engaged in,
3.
The artefact or “device” that the user manipulates or utilizes in order to perform the
task(s).
ACT-R/PM System Diagram
attention
ACT-R/PM system
diagram described
by Byrne (2001).
There are 4
perceptual-motor
modules which
communicate with
the central
components of
cognition. Central
cognition and each
module are serial and
use spreading
activation process
which work in
parallel.
Vision
Module
screen objects
Production
Memory
Motor
Module
clicks
keypresses
Environment
simulated
speech
Speech
Module
target of
attention
(chucks )
attention
Declarative
Memory
Cognitive Layer
target of
attention
(chucks )
simulated
audio
Audition
Module
Perptual Motor
Layer
ACT-R 5.0
Intentional Module
(not identified)
Declarative Module
(Temporal/Hippocampus)
Productions
(Basal Ganglia)
Goal Buffer
(DLPFC)
Retrieval Buffer
(VLPFC)
Matching (Striatum)
Selection (Pallidum)
Execution (Thalamus)
Visual Buffer
(Parietal)
Visual Module
(Occipital/etc)
Manual Buffer
(Motor)
Manual Module
(Motor/Cerebellum)
Environment
Face and Pattern
Recognition
Face Recognition
• Purpose
o Persons use particular characteristics or
features of the face in order to determine if the
face is familiar. The purpose of our study will
be to determine which feature of the face (e.g.
nose, eyes, forehead, mouth…) will allow
participants to increase accuracy and reaction
time in identifying familiar faces.
o We will also determine how the length of time
for which the stimulus (face) is view increases
accuracy.
Signal Detection Theory (SDT)
• Defined as a mathematically based
theory of signal (stimulus) detection
• Assumptions
o
o
The observer is not a passive receiver
of stimulus
The observer is an active decisionmaker who makes difficult perceptual
judgment under conditions of
uncertainty
SDT Outcome Matrix
Response
Yes
No
Signal
Present
Hit
Miss
Absent
False Alarm
Correct
negative
• When the signal is “present” and the response is “yes,” the
observer has made a hit.
• If the observer responded “yes” when that signal was absent,
then a false alarm has been made.
• The other cells are called misses and correct negatives for
obvious reasons.
Industrial Engineering
Research
Terrain Hazard Detection
• Objective
To collect data to study if providing depth in the
field of vision would enhance the terrain hazard
detection capability.
• Method and Procedure
o Terrain scenes with and without hazards were
video taped simultaneously by four video
cameras mounted horizontally in line at the same
level. The distances of center of lenses of the
video cameras from the center of lens of the left
most video camera (reference) were in multiples
of 2.5 inches. This was done to give binocular
parallax of 1X, 2X, and 3X.
o
Terrain Hazard Detection
• A computer with DPS Velocity software was used to
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•
prepare sets of images representing different
viewing conditions.
Images under different viewing conditions were
projected by two DPL projectors on a special screen.
A braking mechanism was designed in-house to stop
the video stream as soon as the hazard was detected
and also when the hazard was verified by the
subjects.
The response times were recorded from the time
code on the monitor for different viewing conditions.
The data collected were submitted to Army Research
Laboratory, Aberdeen for further analysis.
Eye Tracking
• This is an ongoing experiment and will be integrated
into OO technology.
• Objective
o To study how much time eyes are focused on a
given target with and without distractions.
• Method and Procedure
o Video images of terrains with and without hazard
will be presented separately on a video monitor.
The eye tracking camera will track the movement
of the eyes and record them in a file. Area of
interest can be selected on the image to find how
much time the eyes dwelled on the area. Thus by
assigning a target as an area of interest the time
eye dwelled on the target can be monitored.
Eye Tracking
• Experimental setup
• The following are the components of eye
• tracking device
o Controller
o Eye monitor
o Pan/Tilt Optics
o Scene monitor
o Interface PC and monitor
o PC with monitor for viewing by subject
o Scan Converter
o Artificial eye
Integrating Object-Oriented Technology
with
Cognitive Modeling
Object-Oriented Support of Cognitive Experiments
Off-Road Images
Terrain-Hazard
Detection
Face/Pattern
Recognition
Objects
- Attributes
- Operations
- Relationships
Activity Diagram
- System States
MAP
Object-Oriented Model
(Problem Vocabulary)
Object-Oriented - ACT-R Interface
Simulation
- Declarative Memory
- Chunks
- Procedural Memory
- Productions
ACT-R
(Simulator)
Java Language
(Under Development)
Lisp Language
Make
Recommendations
Integrate As Needed
Simulation
Cognitive
Experiment
Results
Compare Results
Design Actual
Cognitive
Experiment
Run
Cognitive
Experiment
Actual
Cognitive
Experiment
Results
Make
Recommendations
Object-Oriented
Development
Process
Problem
Definition
Requirements
Elicitation
Iterative
Process
Analysis
Object
Model
Dynamic
Model
(Object Diagram)
(Activity Diagram)
System Design
Design Model
Implementation
(Object - ACT-R Interface)
Cognitive Model
(ACT-R)
Soldier
Testing
Interactive
Human Computer
Interface
----- ACT-R Basic Framework for Cognitive Model Development ------
Atomic Components of Thought (ACT-R)
• ACT-R is a production system theory that tries to explain human.
Cognition through a model of knowledge structures.
• Two types of knowledge declarative and procedural.
• Declarative knowledge.
• Corresponds to things we know and can describe.
• Represented by structures call chunks.
• Chunk defined by a: type and slots ( ES –frame).
• Example: dog chased the cat – type: chase, agent: dog, object: cat.
• Procedural knowledge.
• Knowledge displayed by our behavior but we are not conscious of.
• No one can describe the rules by which we speak a language, but
we do.
• Defined by production rules:
• Example: IF the goal is to classify a person and he is unmarried.
Then classify him as a bachelor (action part).
• Chunks and productions are the basic building blocks of ACT-R.
Goal
Stack
Memory
ACT-R Flow of Information
Push
Conflict Resolution
Transform
Goal
Pop
Retrieval Result
Current
Goal
Popped
Goal
Production Compilation
Procedural
Memory
Action
Retrieval Request
OUTSIDE WORLD
Declarative
Memory
Perception
Example Problem: Design a Simple Counter
Start
Set Counter = 0
Yes
Stop
Is
Counter = 5
No
Set Counter =
Counter + 1
Object-Oriented Description of Counter Problem
Object-OrientedDescription
Descriptionof
ofCounter
CounterProblem
Problem
Object-Oriented
input_current_value
input_current_value
input_current_value
Counter
Counter
Counter
Tester
Tester
Tester
increment
increment
increment
Incrementer
Incrementer
Incrementer
Name
Name
Name
Counter
Counter
Counter
current_value = 0
Attributes
current_value==00
Attributes
current_value
Attributes
Behavior
Behavior
Behavior
counts ( )
counts( () )
counts
activate
activate
activate
Incrementer
Incrementer
Incrementer
Tester
Tester
Tester
size = 1
size==11
size
end_value = 5
end_value==55
end_value
Increments ( )
Increments( () )
Increments
Tests ( )
Tests( () )
Tests
Counter Activity Diagram
Counter
Tester
Incrementer
Test Counter Value
start
set counter = 0
Test Counter Value
Is
Counter = 5
Yes
stop
Terminate Counter
No
set counter = counter + 1
ACT-R Count Program
(clear-all)
(chunk-type count-order first second)
(chunk-type count-from start end step)
(add-dm
(b ISA count-order first 1 second 2)
(c ISA count-order first 2 second 3)
(d ISA count-order first 3 second 4)
Declarative Knowledge
(e ISA count-order first 4 second 5)
(f ISA count-order first 5 second 6)
Chunks
(first-goal ISA count-from start 2 end 5 step start))
(p start
=goal>
ISA
count-from
start
=num1
step
start
==>
=goal>
step
counting
Production Rule p start
+retrieval>
ISA
count-order
first
=num1
)
(p increment
=goal>
ISA
count-from
start
=num1
- end
=num1
step
counting
=retrieval>
Production Rule p increment
ISA
count-order
first
=num1
second
=num2
==>
=goal>
start
=num2
+retrieval>
ISA
count-order
first
=num2
!output!
(=num1)
)
(p stop
=goal>
ISA
count-from
start
=num
end
=num
step
counting
Production Rule p stop
==>
=goal>
step
stop
!output!
(=num)
)
(goal-focus first-goal)
Integration of Engineering with Psychology for Cognitive Research
Integration of Engineering with Psychology for Cognitive Research
Engineering
Engineering
Develop Workbench Environment
Develop Workbench
Environment
Cognitive
Modeling Tools
Cognitive Modeling Tools
Rational
Rose Environment
Rational Rose Environment
Flowcharting
Tools
Flowcharting
Tools
Conceptual
Development
Conceptual
Development
Problem
Definition
Problem
Definition
Analysis
Analysis
Design
Design
Model Definition
Model Definition
Psychology
Psychology
Define Cognitive Problem
Define Cognitive Problem
Develop
Cognitive
Experiment
Develop
Cognitive
Experiment
Supported
with with
ACT-R
ModelsModels
Supported
ACT-R
Test Cognitive Model
Test Cognitive Model
Develop ACT-R Simulation Models
Develop ACT-R
Simulation
Problem
DefinitionModels
Analysis
Problem Definition
Design
Analysis
Model Definition
Design
Model Definition
Archive and Reuse Models
Modular Design
Archive and
Reuse
Models
Cognitive
Database
Documentation
and Reporting
Modular Design
Cognitive Database
Evaluate Test Results
Evaluate Test Results
Make Recommendations
Make Recommendations
ACT-R Demonstration