🚀 go-pugleaf

	Department of Computer Science/The University of Chicago

		S E M I N A R   A N N O U N C E M E N T


DATE:	WEDNESDAY, OCTOBER 7

TIME:	2:30

PLACE:	RYERSON 276

GUEST SPEAKER:	MANUELA VELOSO (from Carnegie Mellon University)

TALK TITLE:	LEARNING BY ANALOGICAL REASONING IN 
		GENERAL PROBLEM SOLVING

ABSTRACT:
In this talk, I will present my thesis work in integrating 
derivational analogy into general problem solving as a method
of learning at the strategy level to solve problems more effectively.
The derivational analogy method has been fully implemented
in the {\sc prodigy} architecture and proven empirically to be 
amenable to scaling up both in terms of domain and problem complexity.

Reasoning by analogy involves  a  set  of  challenging  problems,
namely: how to accumulate episodic problem solving experience, how
to define and decide when  two  problem  solving  situations  are
similar,  how  to  organize large amounts of knowledge so that it
may be efficiently retrieved, and finally the ultimate problem of
how  to successfully transfer chains of reasoning from past experience
to new  problem solving situations when  only  a  partial  match  exists
among corresponding problems.  More specifically, the dissertation
automates the generation, storage, dynamic indexation, retrieval
and replay for multiple cases (i.e. derivational traces of past
problem  solving  episodes).  Learning occurs by  accumulation and
flexible reuse  of  cases. The problem solving search effort is
reduced incrementally as more episodic experience is compiled 
into the case library.

Scaling up the system proved to be very  demanding.  The  current
system  has  thus  far  been  demonstrated in multiple domains,
including a complex logistics transportation domain where it generated
a library of 1000 cases, showed strong improvements in problem-solving
performance, and pushed the solvability envelope to increasingly more 
complex classes of problems.


		*** Tea in Ry 255 after the talk ***

Visitor's Host:  Kristian Hammond




[ The University of Chicago AI Laboratory sponsors a series of seminar
speakers each academic quarter. These seminars are generally of
interest to those outside the department and are open to the Chicago
AI community.  The department is located in Ryerson Hall at 1100 E.
58th street on the main University of Chicago quadrangle. Seminars are
usually held in Ryerson 276.]

-- 
Kristian T. Simsarian			University of Chicago AI Laboratory
email: kristian@cs.uchicago.edu		CS Dept. Chicago, IL 60637