Answer Set Programming: Towards Efficient and Scalable Knowledge Representation and Reasoning 


AAAI Spring 2001 Symposium
Stanford, March 26-28 2001
Organizers: Alessandro Provetti and Son Tran Cao.

Answer Set Programming (ASP) (a.k.a. Stable Logic Programming or A-Prolog) is the realization of much theoretical work in Non-monotonic Reasoning and AI applications of Logic Programming in the last 12 years. It is based on the view of program statements as constraints on the solution of a given problem. Subsequently, each model of the program encodes a solution to the problem itself. For instance, an ASP program encoding a planning scenario has as many models as valid plans. This schema is similar to that underlying the application of SAT algorithms to AI, and in fact the ranges of applicability of these two techniques are similar. However, thanks to the inherent causal aspect of Answer Set semantics, we can represent default assumptions, constraints, uncertainty and nondeterminism in a direct way.

Several ASP systems are now available, among them are DeReS, dlv, smodels and XSB. Several others can be found through the Library of Logic Programming Systems and Test Cases. These systems support provably correct inferences and are at least as fast and scalable as SAT checkers. These are exciting results for the NMR community and they are attracting the attention of researchers from fields such as planning, cryptography and system verification.


We invite submissions of research abstract, position papers, system demonstrations and experience reports on all aspects of ASP. Here is an incomplete list of `global' questions that authors might want to address:
- what are the strengths of ASP vis-a-vis satisfiability, CSP, abduction, argument-based reasoning and model checking;
- what applications are going to give a perceivable edge (diagnosis, active databases..); and
- what is a fair benchmark to evaluate progress in implementation, preferably beyond random-generated instances.
Some of the specific topics that we would like to discuss at the workshop (through either panel discussions or individual presentations) are:
* new Answer Sets computation algorithms, performance, correctness etc.
* Software engineering of Answer Set Programming
* application experiences in, and issues arising from
-- planning and robot control
-- diagnosis
-- configuration
-- system verification
-- hard functions, e.g., public-key cryptography
-- active databases/data-intensive applications and
-- agents
* Study of the relation between the inference methods for Answer Sets and those developed for SAT or abduction, and
* Creation of a working group for defining a specific benchmark for evaluating Answer Sets algorithms.

Abstracts are due October 9th. Notification will be sent by November 4th.
E-mail your submission (in poscript) to either chair.

FORMAT: Authors are encouraged to submit up to 7 pages in AAAI style.

PROGRAM COMMITTEE (* = organizing committee)
C. Baral* ( Arizona State University
S. Costantini ( Università di L'Aquila
M. Gelfond ( Texas Tech University
A. Kakas ( University of Cyprus
N. Leone ( TU Wien
V. Lifschitz* ( University of Texas at Austin
S. McIlrath* ( Knowledge Systems Lab - Stanford University
I. Niemela* ( Helsinki University of Technology
M. Pagnucco ( Macquarie University
E. Pontelli ( New Mexico State University
H. Turner ( University of Minnesota-Duluth
M. Truszczynski ( University of Kentucky
J-H. You ( University of Alberta