KI 2017: Advances in Artificial Intelligence

40th Annual German Conference on AI, Dortmund, Germany, September 25–29, 2017, Proceedings

  • Gabriele Kern-Isberner
  • Johannes Fürnkranz
  • Matthias Thimm

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10505)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10505)

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Full Technical Papers

    1. Front Matter
      Pages 1-1
    2. Martin Aleksandrov, Toby Walsh
      Pages 29-43
    3. Martin Aleksandrov, Toby Walsh
      Pages 44-57
    4. Lucas Bechberger, Kai-Uwe Kühnberger
      Pages 58-71
    5. Ahcène Boubekki, Ulf Brefeld, Cláudio Leonardo Lucchesi, Wolfgang Stille
      Pages 72-84
    6. Gereon Hinz, Guang Chen, Muhammad Aafaque, Florian Röhrbein, Jörg Conradt, Zhenshan Bing et al.
      Pages 142-154
    7. Almuth Meier, Oliver Kramer
      Pages 178-192
    8. Felix Mohr, Theo Lettmann, Eyke Hüllermeier
      Pages 193-206
    9. Max Schröder, Stefan Lüdtke, Sebastian Bader, Frank Krüger, Thomas Kirste
      Pages 222-235

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 40th Annual German Conference on Artificial Intelligence, KI 2017 held in Dortmund, Germany in September 2017.

The 20 revised full technical papers presented together with 16 short technical communications were carefully reviewed and selected from 73 submissions.

The conference cover a range of topics from, e. g., agents, robotics, cognitive sciences, machine learning, planning, knowledge representation, reasoning, and ontologies, with numerous applications in areas like social media, psychology, transportation systems and reflecting the richness and diversity of their field.

Keywords

artificial intelligence semantics learning systems robotics sensors knowledge based systems robots genetic algorithms evolutionary algorithms formal logic graph theory wireless sensor networks theorem proving sensor nodes sensor data principal component analysis world wide web natural languages

Editors and affiliations

  1. 1.Fakultät für InformatikTechnische Universität DortmundDortmundGermany
  2. 2.FB InformatikTU DarmstadtDarmstadtGermany
  3. 3.FB InformatikUniversität KoblenzKoblenzGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-67190-1
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-67189-5
  • Online ISBN 978-3-319-67190-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book