The 55th GRACE Seminar on Advanced Software Science and Engineering

The 55th GRACE Seminar on Advanced Software Science and Engineering
October 25, 2011 – 17:22 |


The 55th GRACE Seminar on Advanced Software Science and Engineering

Time: 14:00-17:00, November 18th, 2011
Place:Meeting Room (2009/2010), 20F, National Institute of Informatics(map)

Inquiry: Yoshinori Tanabe(
Fee: Free
Please register via the following page:


Torsten Schaub (The University of Potsdam, Germany)

Answer Set Programming, the Solving Paradigm
for Knowledge Representation and Reasoning

Answer Set Programming (ASP; [1,2,3,4]) is a declarative problem solving approach, combining a rich yet simple modeling language with high-performance solving capacities. ASP is particularly suited for modeling problems in the area of Knowledge Representation and Reasoning involving incomplete, inconsistent, and changing information. From a formal perspective, ASP allows for solving all search problems in NP (and NP^{NP}) in a uniform way (being more compact than SAT). Applications of ASP include automatic synthesis of multiprocessor systems, decision support systems for NASA shuttle controllers, reasoning tools in systems biology, and many more. The versatility of ASP is also reflected by the ASP solver clasp [5,6,7], developed at the University of Potsdam, and winning first places at ASP’09, PB’09, and SAT’09.
The talk will give an overview about ASP, its modeling language, solving methodology, and portray some of its applications.
[1] Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. Proceedings of the Fifth International Conference and Symposium of Logic Programming (ICLP’88), The MIT Press (1988) 1070-1080
[2] Niemela, I.: Logic programs with stable model semantics as a constraint program- ming paradigm. Annals of Mathematics and Articial Intelligence 25(3-4) (1999) 241-273
[3] Baral, C.: Knowledge Representation, Reasoning and Declarative Problem Solving. Cambridge University Press (2003)
[4] Gelfond, M.: Answer sets. In Lifschitz, V., van Hermelen, F., Porter, B., eds.: Handbook of Knowledge Representation. Elsevier (2008) 285-316
[5] Gebser, M., Kaufmann, B., Neumann, A., Schaub, T.: Conflict-driven answer set solving. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI’07), AAAI Press/The MIT Press (2007) 386-392
[6] Gebser, M., Kaufmann, B., Schaub, T.: The conflict-driven answer set solver clasp: Progress report. Proceedings of the Tenth International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR’09). Springer (2009) 509-514
[7] Potassco, the Potsdam Answer Set Solving Collection.

Torsten Schaub received his diploma and dissertation in informatics in 1990 and 1992, respectively, from the Technical University of Darmstadt, Germany. He received his habilitation in informatics in 1995 from the University of Rennes I, France. From 1990 to 1993 he was a Researcher at the Technical University at Darmstadt. From 1993 to 1995, he was a Research Associate at IRISA/INRIA at Rennes. From 1995 to 1997, he was University Professor at the University of Angers. At Angers he founded the research group FLUX dealing with the automatisation of reasoning from incomplete, contradictory, and evolutive information. Since 1997, he is University Professor for knowledge processing and information systems at the University of Potsdam. In 1999, he became Adjunct Professor at the School of Computing Science at Simon Fraser University, Canada; and since 2006 he is also an Adjunct Professor in the Institute for Integrated and Intelligent Systems at Griffiths University, Australia. His research interests range from the theoretic foundations to the practical implementation of methods for reasoning from incomplete and/or inconsistent information, in particular Answer set programming.

Oliver Ray(University of Bristol, UK)

Title: Answer Set Programming for Metabolic Pathway Revision

This talk outlines an application of Answer Set Programming (ASP) to the task of automatically revising metabolic pathway models in order to better account for new experimental results. It will illustrate how ASP can be used represent and reason about complex biological interactions and it will explain how ASP was used to revise a state-of-the-art biological model in order to make it logically consistent with observational data acquired by a robot scientist.

Oliver Ray received his BEng and PhD degrees from the Department of Computing at Imperial College London in 2000 and 2005, respectively. He was a Visiting Scientist in the Department of Computer Science at the University of Cyprus in 2006, and he was a JSPS Research Fellow in the Principles of Informatics Research Division at NII in 2007. Since then, he has been an RCUK Research Fellow in the Department of Computer Science at University of Bristol. His research interests include the automation and integration of abductive and inductive inference and their application to the automation of scientific reasoning.

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