AIEDAM
Special Issue, Fall 2009, Vol. 23, No. 4
{moved from Summer 2009, Vol. 23, No. 3}
Problem Solving Methods: Past, Present and Future
Edited by:
Dave Brown
This special issue of
AIEDAM will be devoted to invited papers
concerned with
Problem Solving Methods. It will examine whether they have
fulfilled their early promise, will examine the difficulties that
still remain, and will make predictions about their use in the
future development of knowledge-based systems, in particular those built and
delivered over the Web.
A Problem Solving Method
(PSM) describes how to reason using knowledge to achieve a goal. A
Task, usually specified by its goal and its inputs and outputs, is
something to be done, such as determining a disease from symptoms.
There are usually a variety of ways that a task can be done; i.e.,
one or more PSMs might be appropriate. The kind of tasks being
addressed require the use of knowledge to be tackled properly, and may
need the application of heuristics. Such tasks are often associated
with expert reasoners, such as Doctors or Designers.
Examples of a Task are
specifying the values of a given set of parameters in response to some
requirements (i.e., parametric design), or deciding to which class of
a given set of classes of situations a given situation belongs (i.e.,
classification). Appropriate PSMs, as identified in the literature,
might be "Propose & Revise", and "Cover & Differentiate",
respectively.
A PSM may be primitive or
may decompose the task into subtasks, for which other PSMs may be
appropriate. A PSM usually has a simple control structure that
determines its pattern of inferences. It also specifies the knowledge
needed and what role it plays in the PSM. Each PSM comes with certain
stated assumptions about its potential connections with tasks and with
knowledge. PSMs are linked to domains using ontologies.
One general goal of the
work in PSMs is to be able to aid in the building of a knowledge-based
system for a task by configuring a set of PSMs, or a single PSM,
selected from a library, and linking that with the appropriate
knowledge. This might be human-controlled, or done
(semi-)automatically. Recent work has focussed on doing these
processes over the web.
A partial list of PSM references, including many key papers, can be
found at:
www.cs.wpi.edu/~dcb/courses/CS538/References07.html
Please note that this is not an open call for papers, and that all
contributions will be invited.
The contributors will be:
B. Chandrasekaran,
Bill Clancey,
Deiter Fensel,
Frank van Harmelen,
Enrico Motta,
Mark Musen,
and
Frank Puppe.
The authors will be asked to respond to some or all of a set of
questions and challenges about PSMs provided by the Editor:
www.cs.wpi.edu/~aiedam/SpecialIssues/Brown-PSMs.html
All submissions will be anonymously reviewed
in order to improve the quality of the papers.
Information about the format and
style required for
AIEDAM papers can be found at
www.cs.wpi.edu/~aiedam/Instructions/.
Important dates:
Submission deadline for full papers: 1 May 2008 ***
Reviews due 30 August 2008
Notification and reviews to authors: 30 September 2008
Revised version submission deadline: 15 January 2009
Issue to publisher: 1 March 2009
Editor:
Please direct all enquiries and
submissions to the Editor:
Dr. David C. Brown
AIEDAM PSM Special Issue
Computer Science Department
WPI
100 Institute Rd.
Worcester
MA 01609-2280
USA
Phn: +1 (508) 831-5618
Fax: +1 (508) 831-5776
E-mail: aiedam @ cs.wpi.edu