TY  - JOUR
A1  - Gebser, Martin
A1  - Kaminski, Roland
A1  - Kaufmann, Benjamin
A1  - Lühne, Patrick
A1  - Obermeier, Philipp
A1  - Ostrowski, Max
A1  - Romero Davila, Javier
A1  - Schaub, Torsten H.
A1  - Schellhorn, Sebastian
A1  - Wanko, Philipp
T1  - The Potsdam Answer Set Solving Collection 5.0
JF  - Künstliche Intelligenz
N2  - The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0528-x
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 181
EP  - 182
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - JOUR
A1  - Haubelt, Christian
A1  - Neubauer, Kai
A1  - Schaub, Torsten H.
A1  - Wanko, Philipp
T1  - Design space exploration with answer set programming
JF  - Künstliche Intelligenz
N2  - The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0530-3
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 205
EP  - 206
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - GEN
A1  - Neubauer, Kai
A1  - Haubelt, Christian
A1  - Wanko, Philipp
A1  - Schaub, Torsten H.
T1  - Utilizing quad-trees for efficient design space exploration with partial assignment evaluation
T2  - 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)
N2  - Recently, it has been shown that constraint-based symbolic solving techniques offer an efficient way for deciding binding and routing options in order to obtain a feasible system level implementation. In combination with various background theories, a feasibility analysis of the resulting system may already be performed on partial solutions. That is, infeasible subsets of mapping and routing options can be pruned early in the decision process, which fastens the solving accordingly. However, allowing a proper design space exploration including multi-objective optimization also requires an efficient structure for storing and managing non-dominated solutions. In this work, we propose and study the usage of the Quad-Tree data structure in the context of partial assignment evaluation during system synthesis. Out experiments show that unnecessary dominance checks can be avoided, which indicates a preference of Quad-Trees over a commonly used list-based implementation for large combinatorial optimization problems.
Y1  - 2018
SN  - 978-1-5090-0602-1
U6  - https://doi.org/10.1109/ASPDAC.2018.8297362
SN  - 2153-6961
SP  - 434
EP  - 439
PB  - IEEE
CY  - New York
ER  - 
TY  - JOUR
A1  - Banbara, Mutsunori
A1  - Inoue, Katsumi
A1  - Kaufmann, Benjamin
A1  - Okimoto, Tenda
A1  - Schaub, Torsten H.
A1  - Soh, Takehide
A1  - Tamura, Naoyuki
A1  - Wanko, Philipp
T1  - teaspoon
BT  - solving the curriculum-based course timetabling problems with answer set programming
JF  - Annals of operation research
N2  - Answer Set Programming (ASP) is an approach to declarative problem solving, combining a rich yet simple modeling language with high performance solving capacities. We here develop an ASP-based approach to curriculum-based course timetabling (CB-CTT), one of the most widely studied course timetabling problems. The resulting teaspoon system reads a CB-CTT instance of a standard input format and converts it into a set of ASP facts. In turn, these facts are combined with a first-order encoding for CB-CTT solving, which can subsequently be solved by any off-the-shelf ASP systems. We establish the competitiveness of our approach by empirically contrasting it to the best known bounds obtained so far via dedicated implementations. Furthermore, we extend the teaspoon system to multi-objective course timetabling and consider minimal perturbation problems.
KW  - Educational timetabling
KW  - Course timetabling
KW  - Answer set programming
KW  - Multi-objective optimization
KW  - Minimal perturbation problems
Y1  - 2018
U6  - https://doi.org/10.1007/s10479-018-2757-7
SN  - 0254-5330
SN  - 1572-9338
VL  - 275
IS  - 1
SP  - 3
EP  - 37
PB  - Springer
CY  - Dordrecht
ER  -