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9/22/2013 [a couple of links incorrect or unavailable here]

Philosophy 455/555

Philosophy and Artificial Intelligence

Spring, 2002

taught by John Pollock




Early Arizona AI Researcher

Petroglyph in Santa Catalina foothills,

near Finger Rock Canyon,

north of Tucson (age unknown).

Meeting in Soc. Sci. 311, MWF 2:00 PM

Course Description

This course aims at familiarizing students with the current state of development of artificial intelligence. This work will be related to traditional philosophical problems, and it will be shown how work in each discipline (philosophy and artificial intelligence) is relevant to work in the other.

The course will be organized around the enterprise of building an artificial rational agent. We will begin by building a very simple agent, and then we will make it progressively more sophisticated over the course of the semester. We will focus primarily on automated reasoning and automated planning. The objective is to construct an agent that can acquire information through (simulated) perception, reason about how to achieve its goals, and act on the basis of its deliberations.

A knowledge of formal logic equivalent to that gained by taking an introduction to symbolic logic (Phil/Math 202) will be assumed. Each year some students find themselves in difficulty towards the end of the semester because they have not taken this requirement seriously. To see whether you know the requisite material, or to learn more about symbolic logic, go the the website for Phil 202. You can download an ftp version of the text. You will be assumed to know at least the material in the first four chapters.

Some familiarity with computer programming will also be assumed. One of the objectives of the course will be to teach the students the rudiments of AI programming in the LISP programming language. I assume that most of the students have no previous familiarity with LISP.

Texts

The main text is Artificial Intelligence--A Modern Approach, by Stuart Russell and Peter Norvig. This is generally regarded as the best textbook in AI currently available. However, it is expensive, and we will only have time to talk about the material in a small part of the book. You may want to adjust your book purchasing strategies with this in mind,

The LISP text is Common LISPcraft, by Wilensky.

Programming Lab

There will be a number of exercises that will require some programming in LISP. On most Fridays, the course will meet in the Instructional Computing Lab in Soc. Sci. 226, and that time will be devoted to learning programming and going over the exercises. The lab meetings will be run by Josh ..., who is the TA for the course. The university has acquired a site license for Allegro Common LISP, which runs in Windows. This has been installed on the computers in the Instructional Computing Lab. It will also be made available to you for use on your own machine. Some provision will also be made for Mac users.

The course will be graded entirely on the basis of the exercises.


Office:
email:

Teaching assistant:

Office hours:

Pollock: Monday 1:00 to 2:00 and Friday 1:30 - 2:00 or by appointment.

Josh: Monday and Wednesday, 3:00 - 4:00, or by appointment.

 



Homework Assignments

These are to be turned in by email to Josh at one hour before class on the due date. No late homework will be accepted under any circumstances.

The assignments are listed on a separate website maintained by Josh. 


Download Course Material

 

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  • Natural Deduction in the Predicate Calculus.
    • Natural Deduction, a pdf file.
    • OSCAR, the main file. (version of 9/4/98)
    • Rules, the inference rules used in deductive reasoning. (version of 3/9/98)
    • Rmacros, the macros used for producing reason-schemas. (version of 9/4/98)
    • Syntax, defnition of syntax. (version of 1/20/97)
    • Args, functions for formatting and displaying arguments constructed by OSCAR. (version of 1/20/97)
    • Probs, a list of sample problems. (version of 1/20/97)
    • Trees, the code for evaluating defeat statuses. (version of 1/20/97)
    • Pcompiler, problem compiler for producing user defined problem lists. (version of 3/9/98)
    • graphics, defines graphics used in Macintosh version. (version of 3/9/98)
  • The OSCAR Manual.
    [9/21/13 It appears that John revised earlier versions of the Manual and discarded this particular version. A more recent version is available from Manual.]
    The OSCAR Manual can be downloaded as a set of postscript files or a set of pdf files.
    • Chapter 1: Loading and Running OSCAR (version of 7/20/96)
    • Chapter 2: The Theoretical Basis (version of 7/20/96)
    • Chapter 3: Epistemic Cognition (version of 7/20/96)
    • Chapter 4: Sentential Reasoning (version of 8/27/96)
    • Chapter 5: First-Order Reasoning (version of 8/27/96)
    • Chapter 6: The Discrimination Net (version of 7/20/96)
    • Chapter 7: Perceiving and Reasoning about a Changing World (version of 7/20/96)
    • Bibliography (version of 7/20/96)
    • Appendix 1: Constructing Problem Sets (version of 7/20/96)
  • Defeasible Reasoning
  • Planning