@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{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 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}
}