Cognitive Science 207
Fall 2004

Introduction to Cognitive Modeling

Syllabus

There is no required textbook for the course.  All readings are on-line, in either HTML or Adobe Acrobat format.  Acrobat readers are available for free for most platforms.

Schedule of topics and readings:  

This schedule subject to change.

Dates

Topic Readings
Week 0 (Sep 23-28)
What is cognitive modeling? A.M. Turing, "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.

Week 1 (Sep 30 - Oct 5)
Knowledge Representation.  How can computers know things? Lenat, D. From 2001 to 2001: Common Sense and the Mind of HAL, In Hal's Legacy: 2001's Computer as Dream and Reality edited by: David G. Stork.

Chapter 1, Markman, A.B. Knowledge Representation.  LEA

Foundations of KR section from OpenCyc's Cyc 101 tutorial:
Why use logic?, CycL Syntax, Collections and Individuals, Microtheories.

Week 2 (Oct 7 - Oct 12) Naive Physics. How can we model our understanding of the everyday world?  Forbus, K. 1988.  Qualitative physics: Past, present, and future.  In Shrobe, H. (Ed.) Exploring Artificial Intelligence, Morgan-Kauffmann.

Bredeweg, B. and Forbus, K. 2004. Qualitative Modeling in Education. AI Magazine, Winter 2004.

Week 3 (Oct 14 - Oct 19)

Guest speaker: Chris Riesbeck

Natural language processing. How can we model the process of understanding language? Lillian, L. “I’m sorry Dave, I’m afraid I can’t do that”: Linguistics, Statistics,and Natural Language Processing circa 2001, NRC Study on Fundamentals of Computer Science, version of 2003.

Riesbeck, C. "From Conceptual Analyzer to Direct Memory Access Parsing: An Overview." 

Batali, J. "Notes on Natural Language Processing"
OCTOBER 21

MIDTERM

 
October 26
Post-mortem for midterm  
Week 5 (Oct 28 - Nov 2)
Guest speaker: Don Norman
Emotions
How can we model the interplay of cognition and emotions?  And how does it guide the development of autonomous robots?
Chapter 1: Attractive things work better. 
Chapter 6: Emotional machines.
Chapter 7: The future of robots
From Norman, D.A. 2004. Emotional Design: Why We Love (or Hate) Everyday Things.  New York: Basic Books.

Norman, D.A., Ortony, A. and Russell, D. M. Affect and machine design: Lessons for the development of autonomous machines, IBM Systems Journal, 42(1), 2003.

Excerpt from Ortony, A., Clore, G. and Collins, A. The Cognitive Structure of Emotions.  Cambridge University Press.

 Week 6 (Nov 4 - Nov 9)

 

Analogy and similarity. How do we reason and learn from analogies and metaphors? Gentner, D. and Markman, A. 1997. Structure Mapping in Analogy and Similarity.  American Psychologist, January, pp 45-56

Goldstone, R. L, & Son, J. (in press).  Similarity.  In K. Holyoak & R. Morrison (Eds.).  Cambridge Handbook of Thinking and Reasoning.  Cambridge: Cambridge University Press.
Week 7 (Nov 11 - Nov 16) Learning and education. 
How do we learn new theories and skills?  Can we also use these models to teach?
Koedinger, K. 2000. Intelligent Cognitive Tutors as Modeling Tool and Instructional Model, In NCTM Standards Technology Conference.
(Also available here)
Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51, 355-365.

Week 8 (Nov 18 - Nov 23)
Consciousness
How can ideas from computation shed light on the nature of consciousness? 
McDermott, D. Chapter 3, Mind and Mechanism, MIT Press.
Week 9 [Nov 25, Thanksgiving]

READING WEEK

 
Friday December 10, 12:00 - 2:00.

FINAL EXAM

 

Last edited 09/22/04, by paritosh.