TY  - JOUR
A1  - Linke, Thomas
A1  - Tompits, Hans
A1  - Woltran, Stefan
T1  - On Acyclic and head-cycle free nested logic programs
Y1  - 2004
SN  - 3-540-22671-01
ER  - 
TY  - JOUR
A1  - Linke, Thomas
A1  - Tompits, Hans
A1  - Woltran, Stefan
T1  - On acyclic and head-cycle free nested logic programs
Y1  - 2004
ER  - 
TY  - JOUR
A1  - Pearce, David
A1  - Sarsakov, Vladimir
A1  - Schaub, Torsten
A1  - Tompits, Hans
A1  - Woltran, Stefan
T1  - A polynomial translation of logic programs with nested expressions into disjunctive logic programs
Y1  - 2002
SN  - 3-540-43930-7
ER  - 
TY  - JOUR
A1  - Brain, Martin
A1  - Gebser, Martin
A1  - Pührer, Jörg
A1  - Schaub, Torsten
A1  - Tompits, Hans
A1  - Woltran, Stefan
T1  - Debugging ASP programs by means of ASP
Y1  - 2007
SN  - 978-3-540- 72199-4
ER  - 
TY  - JOUR
A1  - Schaub, Torsten
A1  - Woltran, Stefan
T1  - Answer set programming unleashed!
JF  - Künstliche Intelligenz
N2  - Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)]
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0550-z
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 105
EP  - 108
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - GEN
A1  - Brewka, Gerhard
A1  - Schaub, Torsten
A1  - Woltran, Stefan
T1  - Interview with Gerhard Brewka
T2  - Künstliche Intelligenz
N2  - This interview with Gerhard Brewka was conducted by correspondance in May 2018. The question set was compiled by Torsten Schaub and Stefan Woltran.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0549-5
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 219
EP  - 221
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - GEN
A1  - Schaub, Torsten
A1  - Woltran, Stefan
T1  - Special issue on answer set programming
T2  - Künstliche Intelligenz
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0554-8
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 101
EP  - 103
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - JOUR
A1  - Abseher, Michael
A1  - Musliu, Nysret
A1  - Woltran, Stefan
A1  - Gebser, Martin
A1  - Schaub, Torsten
T1  - Shift Design with Answer Set Programming
JF  - Fundamenta informaticae
N2  - Answer Set Programming (ASP) is a powerful declarative programming paradigm that has been successfully applied to many different domains. Recently, ASP has also proved successful for hard optimization problems like course timetabling and travel allotment. In this paper, we approach another important task, namely, the shift design problem, aiming at an alignment of a minimum number of shifts in order to meet required numbers of employees (which typically vary for different time periods) in such a way that over- and understaffing is minimized. We provide an ASP encoding of the shift design problem, which, to the best of our knowledge, has not been addressed by ASP yet. Our experimental results demonstrate that ASP is capable of improving the best known solutions to some benchmark problems. Other instances remain challenging and make the shift design problem an interesting benchmark for ASP-based optimization methods.
Y1  - 2016
U6  - https://doi.org/10.3233/FI-2016-1396
SN  - 0169-2968
SN  - 1875-8681
VL  - 147
SP  - 1
EP  - 25
PB  - IOS Press
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Delgrande, James Patrick
A1  - Schaub, Torsten
A1  - Tompits, Hans
A1  - Woltran, Stefan
T1  - On computing solutions to belief change scenarios
Y1  - 2001
SN  - 3-540- 42464-4
ER  - 
TY  - JOUR
A1  - Pearce, David
A1  - Sarsakov, Vladimir
A1  - Schaub, Torsten
A1  - Tompits, Hans
A1  - Woltran, Stefan
T1  - A polynomial translation of logic programs with nested expressions into disjunctive logic programs : preliminary report
Y1  - 2002
ER  -