@article{GebserKaminskiSchaub2011,
  author    = {Gebser, Martin and Kaminski, Roland and Schaub, Torsten H.},
  title     = {Complex optimization in answer set programming},
  series = {Theory and practice of logic programming},
  volume    = {11},
  journal   = {Theory and practice of logic programming},
  number    = {3},
  publisher = {Cambridge Univ. Press},
  address   = {New York},
  issn      = {1471-0684},
  doi       = {10.1017/S1471068411000329},
  pages     = {821 -- 839},
  year      = {2011},
  abstract  = {Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.},
  language  = {en}
}
@article{MileoSchaubMericoetal.2011,
  author    = {Mileo, Alessandra and Schaub, Torsten H. and Merico, Davide and Bisiani, Roberto},
  title     = {Knowledge-based multi-criteria optimization to support indoor positioning},
  series = {Annals of mathematics and artificial intelligence},
  volume    = {62},
  journal   = {Annals of mathematics and artificial intelligence},
  number    = {3-4},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1012-2443},
  doi       = {10.1007/s10472-011-9241-2},
  pages     = {345 -- 370},
  year      = {2011},
  abstract  = {Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with Answer Set Programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.},
  language  = {en}
}