TY  - JOUR
A1  - Volkmann, Gerald
A1  - Linke, Thomas
A1  - Waschulzik, Thomas
A1  - Ohmes, Rick
A1  - Schaub, Torsten H.
A1  - Wischnewsky, M.
T1  - HExProSA - ein hybrides Expertensystem zur Prozeßkontrolle und Störfallanalyse von Abwasserbehandlungsanlagen : Erfahrungen bei der Evaluierung eines Prototypen
Y1  - 1998
UR  - http://home.zait.uni-bremen.de/~gerald/papers/pius-papers.html
ER  - 
TY  - JOUR
A1  - Videla, Santiago
A1  - Guziolowski, Carito
A1  - Eduati, Federica
A1  - Thiele, Sven
A1  - Gebser, Martin
A1  - Nicolas, Jacques
A1  - Saez-Rodriguez, Julio
A1  - Schaub, Torsten H.
A1  - Siegel, Anne
T1  - Learning Boolean logic models of signaling networks with ASP
JF  - Theoretical computer science
N2  - Boolean networks provide a simple yet powerful qualitative modeling approach in systems biology. However, manual identification of logic rules underlying the system being studied is in most cases out of reach. Therefore, automated inference of Boolean logical networks from experimental data is a fundamental question in this field. This paper addresses the problem consisting of learning from a prior knowledge network describing causal interactions and phosphorylation activities at a pseudo-steady state, Boolean logic models of immediate-early response in signaling transduction networks. The underlying optimization problem has been so far addressed through mathematical programming approaches and the use of dedicated genetic algorithms. In a recent work we have shown severe limitations of stochastic approaches in this domain and proposed to use Answer Set Programming (ASP), considering a simpler problem setting. Herein, we extend our previous work in order to consider more realistic biological conditions including numerical datasets, the presence of feedback-loops in the prior knowledge network and the necessity of multi-objective optimization. In order to cope with such extensions, we propose several discretization schemes and elaborate upon our previous ASP encoding. Towards real-world biological data, we evaluate the performance of our approach over in silico numerical datasets based on a real and large-scale prior knowledge network. The correctness of our encoding and discretization schemes are dealt with in Appendices A-B. (C) 2014 Elsevier B.V. All rights reserved.
KW  - Answer set programming
KW  - Signaling transduction networks
KW  - Boolean logic models
KW  - Combinatorial multi-objective optimization
KW  - Systems biology
Y1  - 2015
U6  - https://doi.org/10.1016/j.tcs.2014.06.022
SN  - 0304-3975
SN  - 1879-2294
VL  - 599
SP  - 79
EP  - 101
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Thielscher, Michael
A1  - Schaub, Torsten H.
T1  - Default reasoning by deductive planning
Y1  - 1995
ER  - 
TY  - GEN
A1  - Schäpers, Björn
A1  - Niemueller, Tim
A1  - Lakemeyer, Gerhard
A1  - Gebser, Martin
A1  - Schaub, Torsten H.
T1  - ASP-Based Time-Bounded Planning for Logistics Robots
T2  - Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS 2018)
N2  - Manufacturing industries are undergoing a major paradigm shift towards more autonomy. Automated planning and scheduling then becomes a necessity. The Planning and Execution Competition for Logistics Robots in Simulation held at ICAPS is based on this scenario and provides an interesting testbed. However, the posed problem is challenging as also demonstrated by the somewhat weak results in 2017. The domain requires temporal reasoning and dealing with uncertainty. We propose a novel planning system based on Answer Set Programming and the Clingo solver to tackle these problems and incentivize robot cooperation. Our results show a significant performance improvement, both, in terms of lowering computational requirements and better game metrics.
Y1  - 2018
SN  - 2334-0835
SN  - 2334-0843
SP  - 509
EP  - 517
PB  - ASSOC Association for the Advancement of Artificial Intelligence
CY  - Palo Alto
ER  - 
TY  - JOUR
A1  - Schaub, Torsten H.
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  - Schaub, Torsten H.
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  - Schaub, Torsten H.
A1  - Wang, T.
T1  - Preferred well-founded semantics for logic programming by alternating fixpoints : preliminary report
Y1  - 2002
ER  - 
TY  - JOUR
A1  - Schaub, Torsten H.
A1  - Wang, Kewen
T1  - A semantic framework for prefernce handling in answer set programming
Y1  - 2003
ER  - 
TY  - JOUR
A1  - Schaub, Torsten H.
A1  - Wang, Kewen
T1  - A comparative study of logic programs with preference
Y1  - 2001
ER  - 
TY  - JOUR
A1  - Schaub, Torsten H.
A1  - Wang, Kewen
T1  - A comparative study of logic programs with preference
Y1  - 2001
SN  - 1-558-60777-3
SN  - 1045-0823
ER  -