@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} } @misc{BosserCabalarDieguezetal.2018, author = {Bosser, Anne-Gwenn and Cabalar, Pedro and Dieguez, Martin and Schaub, Torsten H.}, title = {Introducing temporal stable models for linear dynamic logic}, series = {16th International Conference on Principles of Knowledge Representation and Reasoning}, journal = {16th International Conference on Principles of Knowledge Representation and Reasoning}, publisher = {ASSOC Association for the Advancement of Artificial Intelligence}, address = {Palo Alto}, pages = {12 -- 21}, year = {2018}, abstract = {We propose a new temporal extension of the logic of Here-and-There (HT) and its equilibria obtained by combining it with dynamic logic over (linear) traces. Unlike previous temporal extensions of HT based on linear temporal logic, the dynamic logic features allow us to reason about the composition of actions. For instance, this can be used to exercise fine grained control when planning in robotics, as exemplified by GOLOG. In this paper, we lay the foundations of our approach, and refer to it as Linear Dynamic Equilibrium Logic, or simply DEL. We start by developing the formal framework of DEL and provide relevant characteristic results. Among them, we elaborate upon the relationships to traditional linear dynamic logic and previous temporal extensions of HT.}, language = {en} } @misc{SchaepersNiemuellerLakemeyeretal.2018, author = {Sch{\"a}pers, Bj{\"o}rn and Niemueller, Tim and Lakemeyer, Gerhard and Gebser, Martin and Schaub, Torsten H.}, title = {ASP-Based Time-Bounded Planning for Logistics Robots}, series = {Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS 2018)}, journal = {Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS 2018)}, publisher = {ASSOC Association for the Advancement of Artificial Intelligence}, address = {Palo Alto}, issn = {2334-0835}, pages = {509 -- 517}, year = {2018}, abstract = {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.}, language = {en} } @article{GebserObermeierSchaubetal.2018, author = {Gebser, Martin and Obermeier, Philipp and Schaub, Torsten H. and Ratsch-Heitmann, Michel and Runge, Mario}, title = {Routing driverless transport vehicles in car assembly with answer set programming}, series = {Theory and practice of logic programming}, volume = {18}, journal = {Theory and practice of logic programming}, number = {3-4}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068418000182}, pages = {520 -- 534}, year = {2018}, abstract = {Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such adhoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.}, language = {en} } @misc{BrewkaSchaubWoltran2018, author = {Brewka, Gerhard and Schaub, Torsten H. and Woltran, Stefan}, title = {Interview with Gerhard Brewka}, 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/s13218-018-0549-5}, pages = {219 -- 221}, year = {2018}, abstract = {This interview with Gerhard Brewka was conducted by correspondance in May 2018. The question set was compiled by Torsten Schaub and Stefan Woltran.}, language = {en} } @misc{LifschitzSchaubWoltran2018, author = {Lifschitz, Vladimir and Schaub, Torsten H. and Woltran, Stefan}, title = {Interview with Vladimir Lifschitz}, 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/s13218-018-0552-x}, pages = {213 -- 218}, year = {2018}, abstract = {This interview with Vladimir Lifschitz was conducted by Torsten Schaub at the University of Texas at Austin in August 2017. The question set was compiled by Torsten Schaub and Stefan Woltran.}, language = {en} } @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} } @article{BrewkaEllmauthalerKernIsberneretal.2018, author = {Brewka, Gerhard and Ellmauthaler, Stefan and Kern-Isberner, Gabriele and Obermeier, Philipp and Ostrowski, Max and Romero, Javier and Schaub, Torsten H. and Schieweck, Steffen}, title = {Advanced solving technology for dynamic and reactive applications}, 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/s13218-018-0538-8}, pages = {199 -- 200}, year = {2018}, 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} } @article{SchaubWoltran2018, author = {Schaub, Torsten H. and Woltran, Stefan}, title = {Answer set programming unleashed!}, 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/s13218-018-0550-z}, pages = {105 -- 108}, year = {2018}, abstract = {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)]}, language = {en} }