BMOORE@SRI-AI.ARPA@sri-unix.UUCP (09/26/83)
From: Bob Moore <BMOORE@SRI-AI.ARPA>
COURSE ANNOUNCEMENT
COMPUTER SCIENCE 400
REPRESENTATION, MEANING, AND INFERENCE
Instructor: Robert Moore
Artificial Intelligence Center
SRI International
Time: MW @ 11:00-12:15 (first meeting Wed. 9/28)
Place: Margaret Jacks Hall, Rm. 301
The problem of the formal representation of knowledge in intelligent
systems is subject to two important constraints. First, a general
knowledge-representation formalism must be sufficiently expressive to
represent a wide variety of information about the world. A long-term
goal here is the ability to represent anything that can be expressed
in natural language. Second, the system must be able to draw
inferences from the knowledge represented. In this course we will
examine the knowledge representation problem from the perspective of
these constraints. We will survey techniques for automatically
drawing inferences from formalizations of commonsense knowledge; we
will look at some of the aspects of the meaning of natural-language
expressions that seem difficult to formalize (e.g., tense and aspect,
collective reference, propositional attitudes); and we will consider
some ways of bridging the gap between formalisms for which the
inference problem is fairly well understood (first-order predicate
logic) and the richer formalisms that have been proposed as meaning
representations for natural language (higher-order logics, intentional
and modal logics).