Proseminar “Künstliche Intelligenz” (inkl. Präsentationskurs, 2+1 SWS) WiSe 2018/19

Inhalt

Dank der Erfolge des Deep Learning ist das Thema “Künstliche Intelligenz (KI)” derzeit sehr aktuell. Allerdings ist maschinelles Lernen nur eines von vielen Themen, mit denen sich KI-Forschung beschäftigt, um intelligentes und adaptives Denken, Entscheiden und Handeln in Maschinen zu realisieren. Dabei sind die Forschungsarbeiten nicht selten interdisziplinär insbesondere in Richtung Kognitionswissenschaften/Psychologie, Philosophie und Neurowissenschaften ausgerichtet.

In diesem Proseminar sollen Grundlagen der Künstlichen Intelligenz in ihrer ganzen Breite behandelt werden. Eine hervorragende Einführung in die KI stellt das Buch [RN14] bzw. [RN03] (frei verfügbare 2. Auflage) dar, das als Basisliteratur für das Proseminar benutzt wird und nach dem sich die Vortragsthemen richten werden; insbesondere wird es Vorträge zu den Themen Agenten, intelligente Suche, Logik und Schlussfolgern, Planen, Entscheidungen unter Unsicherheit und (maschinelles) Lernen geben.

Das Proseminar wird mit dem Präsentationskurs zu Vorlesungsbeginn starten und in den ersten Wochen an 2 Terminen pro Woche stattfinden, später dann an nur einem Termin, so dass sich insgesamt rechnerisch ein Umfang von 3 SWS ergibt. Der Präsentationskurs splittet sich in einen allgemeinen Teil zu Eckpunkten guter Präsentationen nach [Wei09] und in einen einführenden LATEX-Kurs, in dem auch die Grundlagen der Erstellung von Folien mit dem Beamer-Paket von LATEX vermittelt werden. Die Folien zu Präsentationen im Präsentationskurs und im Proseminar müssen auch mit LATEX erstellt werden, das Gleiche gilt für die Ausarbeitung.

Für LaTeX gibt es ein umfangreiches Nachschlagewerk unter http://texdoc.net/texmf-dist/doc/latex/latex2e-help-texinfo/latex2e.pdf, für Beamer findet man unter https://www.sharelatex.com/learn/Beamer eine gute Übersicht.

Literatur

[RN03] S. Russell and P. Norvig. Artificial Intelligence – A Modern Approach. Prentice Hall, New Jersey, 2nd edition, 2003.

[RN14] S. Russell and P. Norvig. Artificial Intelligence – A Modern Approach. Prentice Hall, New Jersey, 3rd edition, 2014.

[Wei09] Jerry Weissman, editor. Presenting to Win. Pearson Education, Upper Saddle River, NJ, 2009.

2017

1. Daan Apeldoorn and Vanessa Volz.
   Measuring Strategic Depth in Games Using Hierarchical Knowledge Bases.
   In 2017 IEEE Conference on Computational Intelligence and Games (CIG). 2017, 9–16.
   URL BibTeX

   @inproceedings{ApeldoornVolz2017,
   	author = "Apeldoorn, Daan and Volz, Vanessa",
   	title = "Measuring Strategic Depth in Games Using Hierarchical Knowledge Bases",
   	booktitle = "2017 IEEE Conference on Computational Intelligence and Games (CIG)",
   	pages = "9--16",
   	year = 2017,
   	address = "New York",
   	publisher = "IEEE",
   	url = "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8080409"
   }
   

1. Christoph Beierle, Bettina Sader, Christian Eichhorn, Gabriele Kern-Isberner, Ralf Georg Meyer and Mathias Nietzke.
   On the Ontological Modelling of Co-Medication and Drug Interactions in Medical Cancer Therapy Regimens for a Clinical Decision Support System.
   In Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2017). 2017, 105-110.
   BibTeX

   @inproceedings{BeierleSaderEichhornKernIsbernerMeyerNietzke2017CBMS,
   	author = "Beierle, Christoph and Sader, Bettina and Eichhorn, Christian and Kern-Isberner, Gabriele and Meyer, Ralf Georg and Nietzke, Mathias",
   	title = "On the Ontological Modelling of Co-Medication and Drug Interactions in Medical Cancer Therapy Regimens for a Clinical Decision Support System",
   	booktitle = "Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2017)",
   	pages = "105-110",
   	year = 2017,
   	publisher = "IEEE Press",
   	address = "New York, NY, USA"
   }
   

1. Christoph Beierle, Christian Eichhorn and Gabriele Kern-Isberner.
   On Transformations and Normal Forms of Conditional Knowledge Bases.
   In Salem Benferhat, Karim Tabia and Moonis Ali (eds.). Advances in Artificial Intelligence: From Theory to Practice: 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Arras, France, June 27-30, 2017, Proceedings, Part I. 2017, 488–494.
   URL BibTeX

   @inproceedings{BeierleEichhornKernIsberner2017,
   	author = "Beierle, Christoph AND Eichhorn, Christian AND Kern-Isberner, Gabriele",
   	editor = "Benferhat, Salem AND Tabia, Karim AND Ali, Moonis",
   	title = "On Transformations and Normal Forms of Conditional Knowledge Bases",
   	booktitle = "Advances in Artificial Intelligence: From Theory to Practice: 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Arras, France, June 27-30, 2017, Proceedings, Part I",
   	year = 2017,
   	publisher = "Springer International Publishing",
   	address = "Cham, DE",
   	pages = "488--494",
   	url = "https://link.springer.com/chapter/10.1007/978-3-319-60042-0_53"
   }
   

1. Christoph Beierle, Christian Eichhorn and Gabriele Kern-Isberner.
   A Transformation System for Unique Minimal Normal Forms of Conditional Knowledge Bases.
   In Alessandro Antonucci, Laurence Cholvy and Odile Papini (eds.). Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 14th European Conference, ECSQARU 2017, Lugano, Switzerland, July 10–14, 2017, Proceedings. Springer International Publishing, 2017, pages 236–245.
   URL BibTeX

   @incollection{BeierleEichhornKernIsberner2017b,
   	author = "Beierle, Christoph AND Eichhorn, Christian AND Kern-Isberner, Gabriele",
   	editor = "Antonucci, Alessandro AND Cholvy, Laurence AND Papini, Odile",
   	title = "{A Transformation System for Unique Minimal Normal Forms of Conditional Knowledge Bases}",
   	booktitle = "Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 14th European Conference, ECSQARU 2017, Lugano, Switzerland, July 10--14, 2017, Proceedings",
   	year = 2017,
   	publisher = "Springer International Publishing",
   	address = "Cham, DE",
   	pages = "236--245",
   	url = "https://link.springer.com/chapter/10.1007/978-3-319-61581-3_22"
   }
   

1. Marco Wilhelm, Christian Eichhorn, Richard Niland and Gabriele Kern-Isberner.
   A semantics for conditionals with default negation.
   In Alessandro Antonucci, Laurence Cholvy and Odile Papini (eds.). Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 14th European Conference, ECSQARU 2017, Lugano, Switzerland, July 10–14, 2017, Proceedings. Springer International Publishing, 2017, pages 236–245.
   URL BibTeX

   @incollection{BeierleEichhornKernIsberner2017b,
   	author = "Wilhelm, Marco AND Eichhorn, Christian AND Niland, Richard AND Kern-Isberner, Gabriele",
   	editor = "Antonucci, Alessandro AND Cholvy, Laurence AND Papini, Odile",
   	title = "{A semantics for conditionals with default negation}",
   	booktitle = "Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 14th European Conference, ECSQARU 2017, Lugano, Switzerland, July 10--14, 2017, Proceedings",
   	year = 2017,
   	publisher = "Springer International Publishing",
   	address = "Cham, DE",
   	pages = "236--245",
   	url = "https://link.springer.com/chapter/10.1007/978-3-319-61581-3_24"
   }
   

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."
   }