@article{HaubeltNeubauerSchaubetal.2018, author = {Haubelt, Christian and Neubauer, Kai and Schaub, Torsten H. and Wanko, Philipp}, title = {Design space exploration with answer set programming}, series = {K{\"u}nstliche Intelligenz}, volume = {32}, journal = {K{\"u}nstliche Intelligenz}, number = {2-3}, publisher = {Springer}, address = {Heidelberg}, issn = {0933-1875}, doi = {10.1007/s13218-018-0530-3}, pages = {205 -- 206}, year = {2018}, abstract = {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.}, language = {en} } @misc{NeubauerWankoSchaubetal.2018, author = {Neubauer, Kai and Wanko, Philipp and Schaub, Torsten H. and Haubelt, Christian}, title = {Exact multi-objective design space exploration using ASPmT}, series = {Proceedings of the 2018 Design, Automation \& Test in Europe Conference \& Exhibition (DATE)}, journal = {Proceedings of the 2018 Design, Automation \& Test in Europe Conference \& Exhibition (DATE)}, publisher = {IEEE}, address = {New York}, isbn = {978-3-9819-2630-9}, issn = {1530-1591}, doi = {10.23919/DATE.2018.8342014}, pages = {257 -- 260}, year = {2018}, abstract = {An efficient Design Space Exploration (DSE) is imperative for the design of modern, highly complex embedded systems in order to steer the development towards optimal design points. The early evaluation of design decisions at system-level abstraction layer helps to find promising regions for subsequent development steps in lower abstraction levels by diminishing the complexity of the search problem. In recent works, symbolic techniques, especially Answer Set Programming (ASP) modulo Theories (ASPmT), have been shown to find feasible solutions of highly complex system-level synthesis problems with non-linear constraints very efficiently. In this paper, we present a novel approach to a holistic system-level DSE based on ASPmT. To this end, we include additional background theories that concurrently guarantee compliance with hard constraints and perform the simultaneous optimization of several design objectives. We implement and compare our approach with a state-of-the-art preference handling framework for ASP. Experimental results indicate that our proposed method produces better solutions with respect to both diversity and convergence to the true Pareto front.}, language = {en} } @article{BanbaraInoueKaufmannetal.2018, author = {Banbara, Mutsunori and Inoue, Katsumi and Kaufmann, Benjamin and Okimoto, Tenda and Schaub, Torsten H. and Soh, Takehide and Tamura, Naoyuki and Wanko, Philipp}, title = {teaspoon}, series = {Annals of operation research}, volume = {275}, journal = {Annals of operation research}, number = {1}, publisher = {Springer}, address = {Dordrecht}, issn = {0254-5330}, doi = {10.1007/s10479-018-2757-7}, pages = {3 -- 37}, year = {2018}, abstract = {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.}, language = {en} } @article{GebserKaminskiKaufmannetal.2018, author = {Gebser, Martin and Kaminski, Roland and Kaufmann, Benjamin and L{\"u}hne, Patrick and Obermeier, Philipp and Ostrowski, Max and Romero Davila, Javier and Schaub, Torsten H. and Schellhorn, Sebastian and Wanko, Philipp}, title = {The Potsdam Answer Set Solving Collection 5.0}, series = {K{\"u}nstliche Intelligenz}, volume = {32}, journal = {K{\"u}nstliche Intelligenz}, number = {2-3}, publisher = {Springer}, address = {Heidelberg}, issn = {0933-1875}, doi = {10.1007/s13218-018-0528-x}, pages = {181 -- 182}, year = {2018}, abstract = {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.}, language = {en} } @misc{NeubauerHaubeltWankoetal.2018, author = {Neubauer, Kai and Haubelt, Christian and Wanko, Philipp and Schaub, Torsten H.}, title = {Utilizing quad-trees for efficient design space exploration with partial assignment evaluation}, series = {2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)}, journal = {2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5090-0602-1}, issn = {2153-6961}, doi = {10.1109/ASPDAC.2018.8297362}, pages = {434 -- 439}, year = {2018}, abstract = {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.}, language = {en} }