2017

  1. Daan Apeldoorn and Gabriele Kern-Isberner.
    Towards an Understanding of What is Learned: Extracting Multi-Abstraction-Level Knowledge from Learning Agents.
    In Vasile Rus and Zdravko Markov (eds.). Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference. 2017, 764–767.
    URL BibTeX

    @inproceedings{ApeldoornKernIsberner2017a,
    	author = "Apeldoorn, Daan and Kern-Isberner, Gabriele",
    	title = "Towards an Understanding of What is Learned: Extracting Multi-Abstraction-Level Knowledge from Learning Agents",
    	booktitle = "Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference",
    	pages = "764--767",
    	year = 2017,
    	editor = "Rus, Vasile and Markov, Zdravko",
    	address = "Palo Alto, California",
    	publisher = "AAAI Press",
    	url = "https://aaai.org/ocs/index.php/FLAIRS/FLAIRS17/paper/view/15510/15038"
    }
    

  1. Marco Ragni, Christian Eichhorn, Tanja Bock, Gabriele Kern-Isberner and Alice Ping Ping Tse.
    Formal Nonmonotonic Theories and Properties of Human Defeasible Reasoning.
    Minds and Machines Volume 27, Number 1:79–117, 2017.
    BibTeX

    @article{RagniEichhornBockKernIsbernerTse2017,
    	author = "Ragni, Marco and Eichhorn, Christian and Bock, Tanja and Kern-Isberner, Gabriele and Tse, Alice Ping Ping",
    	title = "Formal Nonmonotonic Theories and Properties of Human Defeasible Reasoning",
    	journal = "Minds and Machines",
    	editor = "Mariarosaria Taddeo",
    	volume = "Volume 27, Number 1",
    	issue = "Special Issue: Reasoning with Imperfect Information and Knowledge",
    	year = 2017,
    	pages = "79--117",
    	publisher = "Springer Science+Business Media",
    	address = "Dordrecht, NL"
    }
    

2016

  1. Daan Apeldoorn and Gabriele Kern-Isberner.
    When Should Learning Agents Switch to Explicit Knowledge?.
    In Christoph Benzmüller, Geoff Sutcliffe and Raul Rojas (eds.). GCAI 2016. 2nd Global Conference on Artificial Intelligence 41. 2016, 174–186.
    URL BibTeX

    @inproceedings{ApeldoornKernIsberner2015b,
    	author = "Apeldoorn, Daan and Kern-Isberner, Gabriele",
    	title = "When Should Learning Agents Switch to Explicit Knowledge?",
    	booktitle = "GCAI 2016. 2nd Global Conference on Artificial Intelligence",
    	pages = "174--186",
    	year = 2016,
    	editor = {Benzm\"uller, Christoph and Sutcliffe, Geoff and Rojas, Raul},
    	volume = 41,
    	series = "EPiC Series in Computing",
    	publisher = "EasyChair Publications",
    	url = "http://easychair.org/publications/download/When_Should_Learning_Agents_Switch_to_Explicit_Knowledge"
    }
    

  1. Marco Ragni, Christian Eichhorn and Gabriele Kern-Isberner.
    Simulating Human Inferences in the Light of New Information: A Formal Analysis (Extended Abstract).
    In Gerhard Friedrich, Malte Helmert and Franz Wotawa (eds.). KI 2016: Advances in Artificial Intelligence – 39th Annual German Conference on AI (Proceedings) (LNAI) 9904. 2016, 297-302.
    BibTeX

    @inproceedings{RagniEichhornKernIsberner2016b,
    	author = "Ragni, Marco AND Eichhorn, Christian AND Kern-Isberner, Gabriele",
    	title = "Simulating Human Inferences in the Light of New Information: A Formal Analysis (Extended Abstract)",
    	booktitle = "KI 2016: Advances in Artificial Intelligence -- 39th Annual German Conference on AI (Proceedings)",
    	series = "Lecture Notes in Computer Science",
    	volume = "(LNAI) 9904",
    	year = 2016,
    	editor = "Friedrich, Gerhard AND Helmert, Malte AND Wotawa, Franz",
    	pages = "297-302",
    	address = "Cham, CH",
    	publisher = "Springer International Publishing"
    }
    

  1. Christoph Beierle, Christian Eichhorn and Gabriele Kern-Isberner.
    Skeptical Inference Based on C-representations and its Characterization as a Constraint Satisfaction Problem.
    In Proceedings of the 9th International Symposium on Foundations of Information and Knowledge Systems (FoIKS 2016) 9616. 2016, 65–82.
    BibTeX

    @inproceedings{BeierleEichhornKernIsberner2016,
    	address = "Berlin, DE",
    	author = "Beierle, Christoph AND Eichhorn, Christian AND Kern-Isberner, Gabriele",
    	booktitle = "Proceedings of the 9th International Symposium on Foundations of Information and Knowledge Systems (FoIKS 2016)",
    	date-modified = "2017-06-07 14:27:12 +0200",
    	editors = "Simari, Guillermo Ricardo AND Gyssens, Marc",
    	pages = "65--82",
    	publisher = "Springer Science+Business Media",
    	series = "Lecture Notes of Computer Science",
    	title = "{Skeptical Inference Based on C-representations and its Characterization as a Constraint Satisfaction Problem}",
    	volume = 9616,
    	year = 2016
    }
    

  1. Christoph Beierle, Christian Eichhorn, Gabriele Kern-Isberner and Steven Kutsch.
    Skeptical, Weakly Skeptical, and Credulous Inference Based on Preferred Ranking Functions.
    In Gal A Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum and Frank Harmelen (eds.). Frontiers in Artificial Intelligence and Applications Volume 285: ECAI 2016. 2016, 1149–1157.
    BibTeX

    @inproceedings{BeierleEichhornKernIsbernerKutsch2016,
    	author = "Beierle, Christoph AND Eichhorn, Christian AND Kern-Isberner, Gabriele AND Kutsch, Steven",
    	title = "Skeptical, Weakly Skeptical, and Credulous Inference Based on Preferred Ranking Functions",
    	booktitle = "Frontiers in Artificial Intelligence and Applications",
    	volume = "Volume 285: ECAI 2016",
    	year = 2016,
    	editor = "Kaminka, Gal A. AND Fox, Maria AND Bouquet, Paolo AND Hüllermeier, Eyke AND Dignum, Virginia AND Dignum, Frank AND {van Harmelen}, Frank",
    	pages = "1149--1157",
    	address = "Amsterdam, NL",
    	publisher = "IOS Press"
    }
    

    1. Rudolf Seising and Héctor Allende-Cid (eds.).
      Using Background Knowledge for AGM Belief Revision
      .
      pages 275–294, Springer International Publishing, 2017.
      BibTeX

      @inbook{EichhornKernIsbernerBehring2017,
      	author = "Eichhorn, Christian AND Kern-Isberner, Gabriele AND Behring, Katharina",
      	editor = "Seising, Rudolf AND Allende-Cid, H{\'e}ctor",
      	title = "Using Background Knowledge for AGM Belief Revision",
      	booktitle = "Claudio Moraga: A Passion for Multi-Valued Logic and Soft Computing",
      	year = 2017,
      	publisher = "Springer International Publishing",
      	address = "Cham",
      	pages = "275--294"
      }
      

    1. Marco Ragni, Christian Eichhorn and Gabriele Kern-Isberner.
      Simulating Human Inferences in the Light of New Information: A Formal Analysis.
      In Subbarao Kambhampati (ed.). Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI'16). 2016, 2604–2610.
      BibTeX

      @inproceedings{RagniEichhornKernIsberner2016,
      	author = "Ragni, Marco AND Eichhorn, Christian AND Kern-Isberner, Gabriele",
      	title = "Simulating Human Inferences in the Light of New Information: A Formal Analysis",
      	booktitle = "Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI'16)",
      	year = 2016,
      	editor = "Kambhampati, Subbarao",
      	pages = "2604--2610",
      	address = "Palo Alto, CA, USA",
      	publisher = "AAAI Press"
      }
      

    1. Christian Eichhorn, Matthias Fey and Gabriele Kern-Isberner.
      CP- and OCF-networks – a comparison.
      Fuzzy Sets and Systems 298():109 - 127, 2016.
      Abstract Abstract Network approaches are used to structure, partition and display formalisms in the area of knowledge representation as well as decision making. Known approaches are, for instance, OCF-networks, Bayesian style networks where every variable is annotated with a conditional ranking table, and CP-networks, directed acyclic networks with local preferences annotated at each vertex. The structures of these networks are similar, but their semantics seem to be quite different. In this paper we discuss if OCF-networks can be used to model the information of CP-networks and vice versa. To answer this question we investigate which restrictions and conditions have to be presupposed to either of the approaches such that one structure can be used to generate the other.
      URL, DOI BibTeX

      @article{Eichhorn2016109,
      	title = "CP- and OCF-networks – a comparison",
      	journal = "Fuzzy Sets and Systems",
      	volume = 298,
      	number = "",
      	pages = "109 - 127",
      	year = 2016,
      	note = "Special Issue on Graded Logical Approaches and Their Applications",
      	issn = "0165-0114",
      	doi = "http://dx.doi.org/10.1016/j.fss.2016.04.006",
      	url = "http://www.sciencedirect.com/science/article/pii/S0165011416300999",
      	author = "Christian Eichhorn and Matthias Fey and Gabriele Kern-Isberner",
      	keywords = "Preferential models",
      	abstract = "Abstract Network approaches are used to structure, partition and display formalisms in the area of knowledge representation as well as decision making. Known approaches are, for instance, OCF-networks, Bayesian style networks where every variable is annotated with a conditional ranking table, and CP-networks, directed acyclic networks with local preferences annotated at each vertex. The structures of these networks are similar, but their semantics seem to be quite different. In this paper we discuss if OCF-networks can be used to model the information of CP-networks and vice versa. To answer this question we investigate which restrictions and conditions have to be presupposed to either of the approaches such that one structure can be used to generate the other."
      }
      

    1. Marco Wilhelm, Gabriele Kern-Isberner and Andreas Ecke.
      Propositional Probabilistic Reasoning at Maximum Entropy Modulo Theories.
      In Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS). 2016.
      BibTeX

      @inproceedings{KernIsberner_Wilhelm_Beierle_2016,
      	author = "Marco Wilhelm and Gabriele Kern{-}Isberner and Andreas Ecke",
      	title = "Propositional Probabilistic Reasoning at Maximum Entropy Modulo Theories",
      	booktitle = "Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS)",
      	year = 2016
      }
      

    2015

    1. Christoph Beierle, Marc Finthammer and Gabriele Kern-Isberner.
      Relational Probabilistic Conditionals and Their Instantiations under Maximum Entropy Semantics for First-Order Knowledge Bases.
      Entropy 17(2):852–865, 2015.
      URL, DOI BibTeX

      @article{Beierle2015a,
      	title = "Relational Probabilistic Conditionals and Their Instantiations under Maximum Entropy Semantics for First-Order Knowledge Bases",
      	author = "Christoph Beierle and Marc Finthammer and Gabriele Kern{-}Isberner",
      	journal = "Entropy",
      	year = 2015,
      	number = 2,
      	pages = "852--865",
      	volume = 17,
      	doi = "10.3390/e17020852",
      	url = "http://dx.doi.org/10.3390/e17020852"
      }
      

    1. Christian Eichhorn and Gabriele Kern-Isberner.
      Using inductive reasoning for completing OCF-networks.
      Journal of Applied Logic 13(4, Part 2):605–627, 2015.
      DOI BibTeX

      @article{EichhornLKernIsberner2015,
      	title = "Using inductive reasoning for completing {OCF}-networks",
      	author = "Eichhorn, Christian AND Kern-Isberner, Gabriele",
      	year = 2015,
      	pages = "605--627",
      	journal = "Journal of Applied Logic",
      	volume = 13,
      	number = "4, Part 2",
      	issn = "1570-8683",
      	note = "Special {JAL} Issue dedicated to Uncertain Reasoning at {FLAIRS}",
      	editor = "Beierle, Christoph AND Butz, Cory AND Kaci, Souhila",
      	publisher = "Elsevier Science Publishers",
      	address = "Essex, UK",
      	doi = "http://dx.doi.org/10.1016/j.jal.2015.03.006"
      }
      

    1. Gabriele Kern-Isberner, Marco Wilhelm and Christoph Beierle.
      Probabilistic knowledge representation using the principle of maximum entropy and Gröbner basis theory.
      Annals of Mathematics and Artificial Intelligence (AMAI), 2015.
      BibTeX

      @article{KernIsberner_Wilhelm_Beierle_2015,
      	author = "Gabriele Kern{-}Isberner and Marco Wilhelm and Christoph Beierle",
      	title = {Probabilistic knowledge representation using the principle of maximum entropy and {G}r\"{o}bner basis theory},
      	journal = "Annals of Mathematics and Artificial Intelligence (AMAI)",
      	year = 2015
      }
      

    1. Christian Eichhorn and Gabriele Kern-Isberner.
      Qualitative and Semi-Quantitative Inductive Reasoning with Conditionals.
      KI - Künstliche Intelligenz 29(3):279-289, 2015.
      URL, DOI BibTeX

      @article{,
      	year = 2015,
      	issn = "0933-1875",
      	journal = {KI - K{\"u}nstliche Intelligenz},
      	volume = 29,
      	number = 3,
      	doi = "10.1007/s13218-015-0376-x",
      	title = "Qualitative and Semi-Quantitative Inductive Reasoning with Conditionals",
      	url = "http://dx.doi.org/10.1007/s13218-015-0376-x",
      	publisher = "Springer Berlin Heidelberg",
      	keywords = "Conditionals; Nonmonotonic reasoning; Induction; System P; Networks; Ordinal conditional function; Conditional structures",
      	author = "Eichhorn, Christian and Kern-Isberner, Gabriele",
      	pages = "279-289",
      	language = "English"
      }
      

    2014

    1. Patrick Krümpelmann, Tim Janus and Gabriele Kern-Isberner.
      Angerona - A flexible Multiagent Framework for Knowledge-based Agents.
      In Nils Bulling (ed.). Proceedings of the 12th European Conference on Multi-Agent Systems to appear. 2014.
      BibTeX

      @inproceedings{krumpelmann2014eumas,
      	author = {Kr\"umpelmann, Patrick and Janus, Tim and Kern-Isberner, Gabriele},
      	booktitle = "Proceedings of the 12th European Conference on Multi-Agent Systems",
      	date-added = "2014-11-18 12:00:31 +0000",
      	date-modified = "2014-11-18 12:00:31 +0000",
      	editor = "Bulling, Nils",
      	keywords = "own, angerona, multiagent framework",
      	publisher = "Springer",
      	series = "Lecture Notes in Artificial Intelligence",
      	title = "Angerona - A flexible Multiagent Framework for Knowledge-based Agents",
      	volume = "to appear",
      	year = 2014
      }