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Fall 2004 Cognitive Science 207 Introduction to Cognitive Modeling

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Reading/Modeling Assignments: 50% Reading papers ... Norman et al's model of emotions in cognitive ... What cognitive phenomena would you most like to model? ... – PowerPoint PPT presentation

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Title: Fall 2004 Cognitive Science 207 Introduction to Cognitive Modeling


1
Fall 2004 Cognitive Science 207Introduction to
Cognitive Modeling
  • Praveen Paritosh

2
Overview
  • Who we are
  • Course mechanics
  • What is cognitive modeling?
  • Syllabus
  • Homework Zero

3
Who we are
  • Praveen Paritosh
  • Brian Kyckelhahn
  • Kate Lockwood

4
Mechanics
  • Combination of lectures and discussions
  • Weekly homeworks
  • Midterm will be Thu October 21st, in class
  • Final exam will be Fri December 10, 12pm-2pm

5
Communications
  • Class web site http//www.cogsci.northwestern.ed
    u/courses/cg207/
  • To contact Brian, Kate or Praveen re class
    matterscogsci207-staff_at_cs.northwestern.edu
  • For class discussions, we will use the discussion
    forums in Blackboardhttps//courses.northwestern.
    edu/webapps/login

6
Grading
  • Midterm 20
  • Final exam 30
  • Reading/Modeling Assignments 50

7
Reading papers
  • No textbook, but a collection of research papers.
  • We want you to READ the papers.

8
Critiques
  • For each paper, three one sentence long critiques
    of what is wrong with the paper.
  • Due at the beginning of the Tue (Discussion)
    class.
  • Will be used as a basis for the discussion, so be
    prepared to defend your critique!
  • Will account for a third of your grade.

9
Classes
  • Thursday
  • Lecture
  • Readings assigned
  • Tuesday
  • Critiques due before class
  • Discussion based on critiques and readings
  • Modeling homework assigned, due following
    Tuesday.

10
Modeling Assignments
  • Turned in via email to cogsci207-staff_at_cs.northwe
    stern.edu
  • No hardcopies or email to other addresses
  • ASCII or HTML preferred, followed by PDF or Word.
    (If HTML, must be self-contained Broken links
    will lose you points)
  • Late homeworks will be downgraded
  • All work you turn in must be your own.

Reading assignments due beginning of discussion
class on Tuesdays. Bring hardcopy of critiques to
class.
11
(No Transcript)
12
What is mind?
  • One of the deepest questions humanity has asked
  • Many fields have tried to answer it
  • Philosophy
  • Psychology
  • Linguistics
  • Biology (evolutionary, neuroscience, )

13
Its probably a computation
  • A key insight
  • Productive, since it raises many questions
  • Whats a computation?
  • What kind of computation?
  • Operating over what kinds of data?
  • On what sort of system is it being carried out?

14
Artificial Intelligence
  • Goal To understand the nature of intelligence
  • In whatever kind of system can exhibit it,
    including people
  • Early successes inspired (and inspired by)
    comparison with human cognition
  • Solving problems, playing chess, parsing
    sentences, seeing in simple scenes,

15
Cognitive Science
  • Born out of the computational insight
  • Computation could provide a new theoretical
    language for cross-discipline communication
  • Meeting ground for fields traditionally concerned
    with studying cognition
  • Multidisciplinary field
  • Each field has theoretical constructs to share
  • Each field has its own empirical methods for
    testing ideas
  • Deeper insights come out of their interactions

16
Can a machine think?
17
What you will learn
  • A basic understanding of how computation can be
    used to model phenomena in cognitive science
  • Crucial for all cognitive scientists, since
    computation is the theoretical language of the
    field
  • Facilitate working with computational modelers,
    if you arent going to become one
  • Good start to becoming a computational modeler,
    if thats what you want to do.

18
Methodology
  • What does it mean to model thinking?
  • Turing test and its limitations
  • Chatterbots

19
Knowledge representation
  • How can computers know things?
  • Overview of how reasoning systems work
  • An introduction to predicate calculus
  • A high-level tour of the Cyc knowledge base
  • Ontology
  • Microtheories

20
Naïve physics
  • How can we model our everyday understanding of
    the physical world?
  • Qualitative representations as formalization of
    conceptual knowledge
  • Vmodel software

21
Natural language processing
  • How can we model the understanding of language?
  • Guest lecturer Chris Riesbeck

22
Music Cognition
  • Representations of how we understand/ interpret
    music.
  • Guest Lecturer Bryan Pardo

23
Analogy and similarity
  • How do we reason and learn from analogies and
    metaphors?
  • Gentners structure-mapping theory
  • Computational simulations of it

24
Learning and education
  • How do we learn new theories and skills? Can we
    use these models to teach?
  • Production-rule models of skill
  • CMU work on intelligent tutoring systems

25
Emotions and Consciousness
  • How can we study them as scientists?
  • Norman et als model of emotions in cognitive
    architecture
  • McDermotts analysis of consciousness

26
Homework Zero
  • Due Tue, Sep 28, noon. Email to
    cogsci207-staff_at_cs.northwestern.edu as always.
  • Questions
  • Why are you taking this course?
  • What cognitive phenomena would you most like to
    model?
  • Have you had any background in programming or
    computing more generally?
  • Task
  • Post a comment to one of the Discussion Boards
    for the course in Blackboard

27
Readings
  • Turing, A. M. "Computing Machinery and
    Intelligence," Mind, New Series, Vol. 59, No.
    236. (Oct., 1950), pp. 433-460. (also available
    here). 
  • Minsky, M. "Why people think computers can't". 
    AI Magazine, Fall, 1982.
  • Miller, G. "The Cognitive revolution A
    historical perspective", Trends in Cognitive
    Sciences, 7(3), March 2003.
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