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Subject: CFP: Automated Deduction in Nonstandard Logics
Message-Id: <93May7.133701edt.41333@neat.cs.toronto.edu>
Date: Fri, 7 May 1993 13:36:51 -0400


                   Automated Deduction in Nonstandard Logics

AAAI
Fall Symposium Series
22 - 24 October, 1993
Raleigh, North Carolina


AAAI presents the 1993 Fall Symposium Series to be held Friday through 
Sunday, October 22-24, 1993 at the Sheraton Imperial Hotel & 
Convention Center, Research Triangle Park, Raleigh, North Carolina.

The topics of the five symposia in the 1993 Fall Symposium Series are:
  - Automated Deduction in Nonstandard Logics ***********
  - Games: Planning and Learning
  - Human-Computer Collaboration: Reconciling Theory, Synthesizing
     Practice 
  - Instantiating Real-World Agents
  - Learning in Computer Vision: What, Why and How?

Most symposia will be limited to approximately 60 participants. Each 
participant will be expected to attend a single symposium. Working notes 
will be prepared and distributed to participants in each symposium. 

A general plenary session will be scheduled in which the highlights of 
each symposium will be presented, and an informal reception will be held 
on Friday evening, October 22.

In addition to invited participants, a limited number of other interested 
parties will be allowed to register in each symposium. Some student 
scholarship money may be available. Registration information will be 
available in late July, 1993. To obtain it, write to:

AAAI
Fall Symposium Series
445 Burgess Drive
Menlo Park, California 94025
(415) 328-3123
fss@aaai.org


Submission Requirements

Submission requirements vary with each symposium, and are listed in the 
descriptions of the symposia. Please send your submissions directly to the 
address given in the description.

DO NOT SEND submissions to AAAI. 

  - All submissions must arrive by June 4, 1993.
  - Acceptances will be mailed by July 2, 1993.
  - Material for inclusion in the working notes of the symposia must be 
    received by August 23, 1993.


Automated Deduction in Nonstandard Logics

A variety of nonstandard logics have been proposed in artificial 
intelligence to represent time, action, and various epistemic notions such 
as knowledge, belief, and intention. Over the past decade, a wide range of 
methods have been developed for performing deduction with modal 
logics, many-valued logics, and other nonstandard logics. Additionally, an 
array of methods utilizing concepts from nonstandard logic have been 
developed in work on nonmonotonic reasoning, abduction and belief 
revision. 

Although many nonstandard logics and associated deduction methods 
have been recently proposed, a number of shortcomings characterize the 
current state of the field.

First, there are well-understood logics for which we do not yet have 
efficient deduction methods, e.g. multiple-knower epistemic logics, many 
nonmonotonic and conditional logics.

Second, there is a need for systematic comparison among different 
deduction methods, both at the level of implementation or efficiency and 
at the level of naturalness or expressiveness for particular domains and 
applications.

Third, quantitative analyses comparing the time and space requirements of 
nonstandard deduction algorithms are rarely to be found in the literature.

Fourth, although complexity results are available for many nonstandard 
logics, we still lack a sense of how frequently worst-case results will be 
encountered in typical applications. 

Fifth, we need a convincing and well-constructed library of cases where 
these logics could be applied and where the performance of different 
deduction methods can be compared.

Finally, there are few reports of the results of building AI systems (e.g. in 
natural language processing) that make use of theorem provers for 
nonstandard logics.

These gaps are clearly related to one another in complex ways. The 
significance of worst-case results can only be gauged in the context of a 
particular application of a general proof method. Systematic comparison 
of different deduction methods must wait upon quantitative analyses of the 
various methods. Progress requires greater communication between 
theorem proving specialists and researchers in areas such as planning, 
natural language understanding and diagnosis.

The goals of the symposium are to address the various issues listed above 
and also to bring together researchers working on automated deduction in 
nonstandard logics and AI researchers interested in making use of such 
deductive systems. As indicated in the above issues, our interests include 
both theoretical concerns and the practical considerations which attach to 
particular implementations and applications (including performance 
analyses, software tools, and successful or unsuccessful case studies). In 
keeping with the nature of the symposium, we encourage position papers 
and the reporting of works in progress.

Prospective participants should submit a single page summarizing their 
research interests, and providing pointers to any relevant previous work. 
Those interested in presenting their work should instead submit an 
extended abstract (of at most ten pages) that describes the work.

The following are examples of possible topics:
  - A theorem proving method for a nonmonotonic logic of belief.
  - A system that performs deduction in a language that combines a modal 
    logic of belief with a temporal logic.
  - A description of a planner that utilizes a theorem prover for a 
    nonstandard logic.
  - Accounts of abduction and belief revision based on nonstandard logic.
  - A description of an automated reasoning tool for a non-standard logic.
  - Experimental results with implementation(s) of different deduction 
    methods for modal logics.
  - Theoretical discussions of the suitability of different logics (e.g. modal 
    versus multi-valued logics) for different tasks (e.g. belief revision and 
    natural language understanding).

Electronic submissions are preferred, and should be sent to 
scherl@cs.toronto.edu. Otherwise, 5 copies should be sent to:

Richard Scherl
Department of Computer Science
University of Toronto
6 Kings College Rd. Room 283
Toronto, Ontario, Canada M5S 1A4
Telephone: (416)978-7390

Invited Speaker: Melvin Fitting, Lehman College, CUNY.

Organizing Committee: Peter Jackson (cochair), Clarkson University, 
jackson@sandman.soe.clarkson.edu; Rich Scherl (cochair); Donald Nute, 
The University of Georgia; Jeff Pelletier, University of Alberta; Lincoln 
Wallen, University of Oxford