Artificial Intelligence for Engineering Design, Analysis and Manufacturing

Special Issue: Invited Papers


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


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Cambridge University Press
Tue Aug 7 13:16:34 EDT 2007