Previous Weeks in SCXT 350
This page will record what we actually did on each day of the
class.
Week 1: Monday, January
19
Reading:
Topics:
-
Introduction
-
Descartes sets the stage
We begin with Descartes, who gives us an argument to say that computational
intelligence is not possible; an argument which will be reflected upon by
Turing, Newell-Simon, Searle, and Chomsky.
Monday
- Martin Luther King day (no classes)
Wednesday
- Introduction to the course
Friday
- Setting the stage: Descartes
Week 2:
Monday, January 26
Reading: Notes (Week02.ppt)
Topic: Algorithms and computation
Is intelligence computable? Can intelligence be modeled in some fashion
using computers? Or is this idea a dead end? In order to decide what "computational intelligence" might mean, we need to
know something about computation. We begin this part of the discussion by
looking at what a modern computer can do, and how it might be programmed.
We use the programming language LISP for several reasons: Firstly, it is a
programming language which is likely to be new to everyone in the class, and,
secondly, since it is one of the primary languages used in artificial
intelligence.
Monday
- A basic model for a computer
- What a computer can do
- Algorithms
Wednesday
- A gentle introduction to LISP
Friday
- More on Lisp (The scheduled laboratory session ran into configuration
problems and will be rescheduled for next Friday)
Week 3: Monday, February 2
- Topic(s)
- Notion of an algorithm
- The Turing Test
- Some history
- Reading
- Anthology
- Please read the introduction to the first section (pages 3 - 7) and the
first paper (A History of Thinking) carefully. Scan more briefly the
paper by Hilary Putnam (Minds and Machines).
- Read carefully the Turing paper on pages 153 - 167 (Turing: Computing Machinery and
Intelligence). The course home page contains a "Read and Respond"
exercise on this paper which will be due this Wednesday. See
http://www.math.ups.edu/~matthews/SCXT350_S2004/rr01.html or the link on
the course home page for more details.
The great British logician Alan Turing (see
http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Turing.html)
gives a response to Descartes and claims not only that a computational model of
intelligence is possible, it is inevitable. Before we discuss his paper we
talk about algorithms and, if time permits, give some of the history of
computers. We'll try again for a lab day in Lisp on Friday (with a new
handout that extends slightly the handout from last Friday)
Monday
Wednesday
- A reminder from Descartes
- The Turing test
- Some more history of computers
Friday
- A second attempt at a lab day (successful!)
Other notes:
Week 4: Monday, February 9
- Topic(s)
- Marr's three levels of explanation
- GOFAI and connectionism
- Reading
- Semantic Engines: An Introduction to Mind Design (Anthology, page 34 -change:
let's read this for next week).
- Vision (Anthology, page 69). There will be a "read and respond"
assigned for this paper.
- Dawson, chapters 1 and 2
We begin a voyage through some work in artificial intelligence, beginning
with the Psychologist David Marr's classic paper on vision (Part I, paper 5 of
the anthology). We then are introduced to two approaches we will study in
further depth in the following: Symbolic AI (which Margaret Boden refers
to as "Good old-fashioned AI") and connectionist AI.
Monday
- Discussion of Lisp homework.
- A handout on Lisp
- The problems of Symbolic Artificial Intelligence. A brief history.
Wednesday
- Discussion of Marr's paper (there will be a "read and respond" on this
paper: See This link for more details)
- Pickup of Lisp homework and return of a key for it.
Friday
- A quick introduction to symbolic AI
Week 5: Monday, February 16
We undertake a quick overview of both symbolic and connectionist AI, with the
help (possibly, if available) of a video. Following this, we examine each
approach to modeling cognition in more detail
Monday
Wednesday
Friday
Other Notes
- The first hour exam will be next Friday
- The read-and-respond for next Wednesday has been postponed until the
Wednesday following. Please follow
this link for more details.
Week 6: Monday, February 23
We continue the introduction to connectionist AI with the definition of a
perceptron and a short written exercise. We then begin a more careful examination of symbolic AI by following a standard
description of symbolic AI as "Knowledge Representation + Search". Please
note that we are swapping week 6 and week 7 in the original lecture schedule
(but that the first exam is still Friday, February 27).
Monday
- Connectionist AI (a continuation of the introduction - more later)
Wednesday
- Perceptrons and an exercise in perceptrons
- Review for first hour exam
Friday
Other Notes
- The Read and respond exercise originally scheduled for Wednesday of this
week has been moved to next week. Please follow
this link for more details.
Week 7: Monday, March 1
Dydd Dewi Sant yn hapus iawn i baub!
We begin a more careful examination of symbolic AI by following a standard
description of symbolic AI as "Knowledge Representation + Search". Please
note that we are swapping week 6 and week 7 in the original lecture schedule
(but that the first exam is still Friday, February 27).
Monday
- Discussion of paper / project (rescheduled from last Wednesday)
- States, operators and search
- Means-ends analysis
- The exam will be returned Wednesday
Wednesday
Friday
- Search: uninformed and informed
- Perceptron exercise due
- Paper/project proposals due.
Other Notes
- The Read and respond exercise originally scheduled for Wednesday of last
week has been moved to this week. Please follow
this link for more details.
- We will have class next Friday after all (I will not be attending the
conference)
Week 8: Monday, March 8
- Topic(s)
- Knowledge representation
- Problem solving
- Expert Systems
- Reading
- Dawson, chapters 1 - 3
- Handouts
Newell and Simon give search as the primary mechanism for problem-solving.
We begin by considering how people solve problems, and then look at how a
computer program can encapsulate expertise.
Monday
- An introduction to search
- Means-ends analysis (an introduction)
Wednesday
- Discussion of Newell and Simon's 1975 Turing Award Lecture (with a
read and respond exercise due in class last week)
Friday
- Search: uninformed and informed
Other Notes
- Next week is Spring Break!
- The annotated bibliography is moved to Wednesday, March 24. Please
note the change in due-date.
- Next class week: More on search, and an introduction to knowledge
representation
Week 9: Monday, March 15
- Topic(s)
- Spring Break! No classes or office hours
Week 10: Monday, March 22
- Topic(s)
- Knowledge representation
- Problem solving
- Expert Systems
- Reading
- Dawson, chapters 1 - 3
- Handouts
Newell and Simon give search as the primary mechanism for problem-solving. We begin by considering how people solve problems, and then look at how a computer program can encapsulate expertise.
Monday
- Continued survey on search
- Introduction to knowledge representation
Wednesday
- Knowledge representation
- Annotated bibliography due Wednesday (note change in due-date)
Friday
- Continuation of discussion on Knowledge Representation
Other Notes
- Our next exam is Friday, April 2 (next Friday)
- Next class week: Expert Systems!
Week 11: Monday, March 29
- Topic(s)
- Knowledge representation
- Problem solving
- Expert Systems
- Reading
Newell and Simon give search as the primary mechanism for problem-solving. We begin by considering how people solve problems, and then look at how a computer program can encapsulate expertise.
Monday
- Review for second hour exam
Wednesday
- Guest lecturer: Mark Reinitz
Friday
Other Notes
- Next class week: Expert Systems!
Week 12: Monday, April 5
- Topic(s)
- Knowledge representation
- Problem solving
- Expert Systems
- Reading
- Dawson, chapters 1 - 3
- Handouts
Newell and Simon give search as the primary mechanism for problem-solving.
We begin by considering how people solve problems, and then look at how a
computer program can encapsulate expertise.
Monday
- Knowledge representation concluded
- Introduction to expert systems
Wednesday
Friday
- In-class exercise on expertise
Other Notes:
- Because of several meetings this week, office hours need to be re-arranged as follows:
- Monday: 10:00 AM
- Wednesday: 10:00 AM
- Thursday: 4:00 PM
- Tuesday (11:00) and Friday (4:00) as usual
- Next week: Paper draft due (April 14)
- Cathy Hale will give a guest lecture on Wednesday, April 14.
Week 13: Monday, April 12
- Topic(s)
- Reading
- Please start reading chapters 4 - 7 in Dawson
- Notes on CLIPS will be available in WEEK13.PPT.
One way to encapsulate problem solving is in an expert system. We examine an expert system shell called CLIPS. This will also give us an opportunity to integrate what has been learned about search and knowledge representation in symbolic AI.
Monday
- Introduction to CLIPS
- Evaluations
Wednesday
- Guest lecturer: Cathy Hale
- Paper draft due
Friday
Other Notes
- The third hour exam will be given on Friday, April 30.
Week 14: Monday, April 19
One way to encapsulate problem solving is in an expert system. We examine an expert system shell called CLIPS. This will also give us an opportunity to integrate what has been learned about search and knowledge representation in symbolic AI.
Monday
- Conclude discussion on CLIPS
- Exercise on CLIPS assigned.
Wednesday
- No class (instructor ill)
Friday
- University President Inauguration - no classes or office hours
Other Notes
- The third hour exam will be given on Friday, April 30
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