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∂03-Jan-79  0125	RWW  
This course will be given.  The time is 99% certain. The place is to be 
determined.  It starts Thursday Jan 4 and I will more info as to the place.
please feel free to call me and ask about it.

Title: Philosophy and AI 
Winter Quarter 
TTH 2:30 - 3:45 
3 units

Instructor:  Richard Weyhrauch 

No Prerequisites.  This course is for graduates and undergraduates with an
interest in AI.  Text will consist of lecture notes and assigned readings.
Students will be expected to listen to the lectures, participate actively
in discussions and read the assigned readings.  Course projects will be
available for anyone interested but they are not a requirement.

In this course I intend to address the question: what kind of thing should
a researcher in artificial intelligence be trying to build?  I'll
introduce the idea of a "computer individual" (an electro-mechanical
associate) and ask what properties such an individual should have.

The course will have three parts.

In the first part you will be asked to suspend your judgement for a while
and learn some formal logic.  This part of the course will be entirely
self contained and will not require any prior knowledge of logic.  In fact
previous knowledge will probably get in your way for a while.  There are
two purposes to this part of the course.  The first is that the rest of
the course depends on your your technical understanding of the ideas I
will present.  The second is that logic has been used only in a very
simple way in AI up to now and I hope to expand your perspective as to how
it might be used.  To do this you need to know some technical things and
it is these I intend to teach.  This will not be a logic course.  It will
not cover the standard material in a logic course.  It is a practical
course in building artificial intelligence systems.  We will sometimes use
logic as a tool in way that it hasn't been used before.  I hope to
substantially alter your view of what logic is good for.  If I don't by
the end of this course I will consider it a failure.  The points of logic
will be illustrated by the use of the FOL reasoning system, which embodies
these ideas.

The second part of the course will be taken up with relating the notions
of logic introduced in the first part to the question of building AI
systems capable of making intelligent conclusions from the data it has.
One section will be taken up with looking at problems that have been dealt
with using the McCarthy situation calculus style of representation.  We
will introduce a new notion of situation and use blocks world problems as
an illustration of how to use this idea.  We will work out D.Michie's keys
and boxes problem in detail.  The discussion will include remarks about
STRIPS and SHRDLU.  We will then use the meta-theoretical structures we
learned earlier in the course to explore the idea of machine learning and
problem solving in mathematical theory of computation.  We will finish by
discussing reasoning about knowledge (one's own and other peoples),
"non-monotonic logic", and in general the problems of reasoning using
modalities.  This is just a brief sketch of the topics that will be
mentioned.  The purpose of this part of the course is to gain facility
with the use of the notions introduced at the start of the course and to
relate them to the kinds of reasoning systems that people currently find
interesting.

The third part of the course will directly address the question of
constructing electro-mechanical individuals - NOT the question of AI
programs.  This shift of viewpoint will be central to our discussion of
the question:  how is it that such a device can build a functional
understanding of his environment?  This part of the course will discuss
many aspects of the problem of artificial cognition.  I am interested in
several questions here.  1) how is perception possible, that is, how do we
get from sense impressions to theories of our world?  In particular I view
natural language understanding as a perception problem, i.e., how do we
get from the stream of auditory input to an understanding of its meaning?
2) What is the origin of natural language?  3) What is a conversation?  A
lot of this course will make remarks about the QUALITY of the conversation
we want to be able to have with our computer friend.  In AI we talk about
common sense reasoning.  I want to look at all of the above problems as
practical questions about what our common sense understanding of our world
is like and how we acquire and use it.  These later questions will take us
far afield, with readings from psychology, philosophy, mysticism, politics, 
etc.

In the end I hope that we will have had a good time exploring what a wide
range of contemorary ideas tell us about AI.  In addition the technical
tools presented in my lectures are meant to describe practical and
implementable ways of embodying some of these ideas into an artificial
intelligence system.