@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{GebserObermeierOttoetal.2018, author = {Gebser, Martin and Obermeier, Philipp and Otto, Thomas and Schaub, Torsten H. and Sabuncu, Orkunt and Van Nguyen, and Tran Cao Son,}, title = {Experimenting with robotic intra-logistics domains}, 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/S1471068418000200}, pages = {502 -- 519}, year = {2018}, abstract = {We introduce the asprilo1 framework to facilitate experimental studies of approaches addressing complex dynamic applications. For this purpose, we have chosen the domain of robotic intra-logistics. This domain is not only highly relevant in the context of today's fourth industrial revolution but it moreover combines a multitude of challenging issues within a single uniform framework. This includes multi-agent planning, reasoning about action, change, resources, strategies, etc. In return, asprilo allows users to study alternative solutions as regards effectiveness and scalability. Although asprilo relies on Answer Set Programming and Python, it is readily usable by any system complying with its fact-oriented interface format. This makes it attractive for benchmarking and teaching well beyond logic programming. More precisely, asprilo consists of a versatile benchmark generator, solution checker and visualizer as well as a bunch of reference encodings featuring various ASP techniques. Importantly, the visualizer's animation capabilities are indispensable for complex scenarios like intra-logistics in order to inspect valid as well as invalid solution candidates. Also, it allows for graphically editing benchmark layouts that can be used as a basis for generating benchmark suites.}, language = {en} } @article{BobdaYongaGebseretal.2018, author = {Bobda, Christophe and Yonga, Franck and Gebser, Martin and Ishebabi, Harold and Schaub, Torsten H.}, title = {High-level synthesis of on-chip multiprocessor architectures based on answer set programming}, series = {Journal of Parallel and Distributed Computing}, volume = {117}, journal = {Journal of Parallel and Distributed Computing}, publisher = {Elsevier}, address = {San Diego}, issn = {0743-7315}, doi = {10.1016/j.jpdc.2018.02.010}, pages = {161 -- 179}, year = {2018}, abstract = {We present a system-level synthesis approach for heterogeneous multi-processor on chip, based on Answer Set Programming(ASP). Starting with a high-level description of an application, its timing constraints and the physical constraints of the target device, our goal is to produce the optimal computing infrastructure made of heterogeneous processors, peripherals, memories and communication components. Optimization aims at maximizing speed, while minimizing chip area. Also, a scheduler must be produced that fulfills the real-time requirements of the application. Even though our approach will work for application specific integrated circuits, we have chosen FPGA as target device in this work because of their reconfiguration capabilities which makes it possible to explore several design alternatives. This paper addresses the bottleneck of problem representation size by providing a direct and compact ASP encoding for automatic synthesis that is semantically equivalent to previously established ILP and ASP models. We describe a use-case in which designers specify their applications in C/C++ from which optimum systems can be derived. We demonstrate the superiority of our approach toward existing heuristics and exact methods with synthesis results on a set of realistic case studies. (C) 2018 Elsevier Inc. All rights reserved.}, language = {en} } @article{GebserKaminskiKaufmannetal.2018, author = {Gebser, Martin and Kaminski, Roland and Kaufmann, Benjamin and Schaub, Torsten H.}, title = {Multi-shot ASP solving with clingo}, series = {Theory and practice of logic programming}, volume = {19}, journal = {Theory and practice of logic programming}, number = {1}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068418000054}, pages = {27 -- 82}, year = {2018}, abstract = {We introduce a new flexible paradigm of grounding and solving in Answer Set Programming (ASP), which we refer to as multi-shot ASP solving, and present its implementation in the ASP system clingo. Multi-shot ASP solving features grounding and solving processes that deal with continuously changing logic programs. In doing so, they remain operative and accommodate changes in a seamless way. For instance, such processes allow for advanced forms of search, as in optimization or theory solving, or interaction with an environment, as in robotics or query answering. Common to them is that the problem specification evolves during the reasoning process, either because data or constraints are added, deleted, or replaced. This evolutionary aspect adds another dimension to ASP since it brings about state changing operations. We address this issue by providing an operational semantics that characterizes grounding and solving processes in multi-shot ASP solving. This characterization provides a semantic account of grounder and solver states along with the operations manipulating them. The operative nature of multi-shot solving avoids redundancies in relaunching grounder and solver programs and benefits from the solver's learning capacities. clingo accomplishes this by complementing ASP's declarative input language with control capacities. On the declarative side, a new directive allows for structuring logic programs into named and parameterizable subprograms. The grounding and integration of these subprograms into the solving process is completely modular and fully controllable from the procedural side. To this end, clingo offers a new application programming interface that is conveniently accessible via scripting languages. By strictly separating logic and control, clingo also abolishes the need for dedicated systems for incremental and reactive reasoning, like iclingo and oclingo, respectively, and its flexibility goes well beyond the advanced yet still rigid solving processes of the latter.}, 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} } @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} }