Special Issue of Annals of Mathematics and Artificial Intelligence


Answer Set Programming

Special Issue Editors:
Gerhard Brewka (University of Leipzig, Germany)
Jürgen Dix (Clausthal University of Technology, Germany)

About the Special Issue

Answer set programming (ASP) is a promising declarative programming paradigm which has proven to be successful in a variety of areas such as planning, diagnosis, configuration and space shuttle control. It emerged from deductive databases as well as from non-monotonic reasoning. Answer sets are sets of literals representing intended models of generalized logic programs with two types of negation. They were introduced by Gelfond and Lifschitz and generalize stable models to more expressive logic programs. The basic idea underlying ASP is to represent a problem in a way such that answer sets correspond to solutions of the problem. A Working Group on ASP funded by the EC ( coordinates and represents most of the work on ASP done in Europe. We invite papers describing original research advancing the state of the art in ASP. Contributions may range from theoretical foundations (e.g. language extensions, first order programs) to implementation methods (e.g. new answer set generation methods, intelligent grounding or related heuristics) and innovative applications (e.g. information extraction, agent technology, dynamic systems). In particular applications showing that ASP scales up or is competing with special-purpose techniques are welcome.
  • Foundations of ASP
  • Planning in ASP
  • Language extensions (aggregates, preferences , etc.)
  • Knowledge representation in ASP
  • Integrated approaches (description logic, constraints, etc.)
  • ASP methodology (modularization, debugging etc.)
  • Innovative applications (bioinformatics, linguistics, etc.)
  • Systems of ASP
  • Algorithms and heuristics

About the Special Issue Editors

Gerhard Brewka is Professor for Intelligent Systems at Leipzig University (Germany) since 1996. Before that he was Professor for Knowledge-Based Systems at Technical University of Vienna. He is director of the Leipzig doctoral programme in Knowledge Representation. His research interests include knowledge representation, nonmonotonic reasoning, inconsistency handling, preference models and logic programming.

Jürgen Dix is Professor for Computational Intelligence at Clausthal University of Technology (Germany). He is also member of the CS Department at the Technical University of Vienna, and honorary member at The University of Manchester, where he lived from 2000-2003. Since 1989 he is working in several areas of Computational Logic (nonmonotonic reasoning, logic programming, deductive databases, knowledge representation) and, in the past 7 years, also in Multi-Agent Reasoning.

About Annals of Math and AI

Annals of Mathematics and Artificial Intelligence (AMAI) is devoted to reporting significant contributions on the interaction of mathematical and computational techniques reflecting the evolving disciplines of artificial intelligence. Annals of Mathematics and Artificial Intelligence publishes edited volumes of original manuscripts, survey articles, monographs and well refereed conference proceedings of the highest caliber within this increasingly important field. All papers will be subject to the peer reviewing process with at least two referees per paper.


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