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EMPIRICAL METHODS IN ARTIFICIAL INTELLIGENCE
ECAI-2000 Workshop, August 22, 2000, Berlin, Germany
Workshop Description
=====================
In many areas of AI, experiments are the primary means of
demonstrating the potential and value of systems and techniques. It
has been widely recognised that appropriate empirical approaches often
yield new insights into algorithms and systems, and often lead to new
experimental and theoretical research issues. Thus empirical methods
for analysing and comparing systems and techniques are of considerable
interest to many AI researchers.
While experimental approaches are well established and have reached a
high level of sophistication in other sciences, like physics and
biology, the types of empirical analysis done in AI are often
rather rudimentary. This workshop aims to improve this situation.
The workshop will bring together researchers from different areas of
AI and Operations Research, such as constraint satisfaction and
satisfiability, knowledge acquisition, machine learning and neural
networks, theorem proving, planning and scheduling, learning,
robotics, natural language processing and speech recognition, vision,
and many others where empirical methods are used to analyse and
evaluate algorithms and systems.
Topics
=======
-- the design of computational experiments
-- performance criteria for algorithms or systems
-- methods for analysing, characterising, and comparing algorithmic
performance
-- the choice of problem sets - benchmark problems, artificially
generated problems, etc.
-- the role of theoretical models in experiments
-- studies from various fields of AI which exemplify good empirical
methodology and its value for obtaining interesting results.
-- the ethics of experimentation; e.g., should reports provide
enough information for experimental replication? are AI
experimental standards distinct from those of other disciplines?
-- to what extent are empirical methods really necessary in AI (possibly
due to the inadequacy or impossibility of theoretical methods)?
How is AI different from other areas of Computer Science
in this respect?
Format
======
This half-day workshop is co-ordinated with the ECAI-2000 Tutorial
"Stochastic Search Algorithms" (presented by Holger H. Hoos and Thomas
Stuetzle) and the ECAI-2000 Tutorial "Empirical Methods for Computer
Science" (presented by Paul Cohen, Ian Gent, and Toby Walsh). The
workshop and the two tutorials will complement each other and together
will offer a comprehensive coverage of many important issues in the
empirical analysis of AI algorithms and systems.
Important Dates
================
-- Submission deadline: May 5, 2000
-- Notification of acceptance: May 26, 2000
-- Camera-ready copy deadline: June 8, 2000
-- Workshop: August 22, 2000
Submission Procedure
=====================
We ask authors to submit a position paper either in Postscript or PDF.
The position paper should describe and justify your view on one or
more topics relevant to this workshop. The paper should be reasonably
concise, i.e. we expect that about 1000 words will suffice, but you
may use more if needed. Submissions should be printed on 8.5" x 11" or
A4 paper with at least 1 inch margins on all sides. The first page of
the position paper should include the title, a brief abstract, and
author names, affiliations, postal addresses, electronic mail
addresses, and telephone and fax numbers.
To submit a paper, email it (or a URL pointer to it) to hoos@cs.ubc.ca
or stuetzle@informatik.tu-darmstadt.de.
The number of participants is limited; participants will be selected
based on the submitted position paper. All participants are expected
to contribute to the discussions in the workshop.
Note that all workshop participants have to register for the main
ECAI-2000 conference
Cochairs
=========
Holger H. Hoos
Dept. of Computer Science
University of British Columbia
Vancouver, BC, V6T 1Z4, Canada
Email: hoos@cs.ubc.ca
WWW: www.cs.ubc.ca/~hoos
Thomas Stuetzle
Dept. of Computer Science, Intellectics Group
Darmstadt University of Technology
D-64283 Darmstadt, Germany
Email: stuetzle@informatik.tu-darmstadt.de
WWW: www.intellektik.informatik.tu-darmstadt.de/~tom
Organisation Committee
=======================
Paul Cohen, University of Massachusetts, Amherst
Kevin Korb, Monash University, Australia
Geoff Sutcliffe, James Cook University, Australia
Toby Walsh, University of York, United Kingdom
Additional Information
=======================
http://www.cs.ubc.ca/~hoos/ecai2000-empai
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