********************************************************************************
CALL FOR CONTRIBUTIONS Hybrid Reasoning and Learning HRL 2018 A Worskhop held on October 28 at KR 2018, Tempe, Arizona, USA https://www.hybrid-reasoning.org/kr2018_ws/ **** Paper submission deadline extended to 04 August 2018 **** ******************************************************************************** For many years, research in the area of knowledge representation and reasoning (KR&R) was mainly concerned with logic-based, qualitative forms of reasoning. However, successfully applying KR&R techniques to areas such as robotics, bioinformatics or logistics usually requires taking into account quantitative aspects of reasoning as well. An example is a symbolic planner on a mobile robot, which is integrated with geometric planning in continuous state space in order to check whether a grasping action is feasible or not. Similarly, in bioinformatics quantitative information is often needed for discriminating solutions obtained from qualitative constraints. Examples include natural aspects like mass preservation or flux balances but also human-oriented ones due to different degrees of confidence in data or models. Other forms of quantitative aspects of reasoning are uncertainty, time, resources, numerical rankings, and data such as text or 3D point clouds. Furthermore, in domains such as robotics and bioinformatics it is often hard to construct the full hybrid models by hand. Especially for the quantitative component the question is: where should the numbers come from? On the other hand, there is often data available, which calls for the use of machine learning techniques that can support learning such hybrid representations, either by estimating the needed quantitative information or by learning also the structure of the respective components of hybrid models. This way, even different learning methods can contribute to successfully implementing hybrid models. This workshop intends to bring together researchers interested in combining both qualitative and quantitative forms of reasoning and learning, which we refer to as hybrid reasoning and learning. We are interested in recent work which advances the theory of hybrid reasoning, the learning of hybrid representations as well as their applications. Besides original work we also welcome relevant published material. INVITED SPEAKERS Scott Sanner, University of Toronto Guy Van den Broeck, UCLA ORGANIZING COMMITTEE Luc De Raedt, KU Leuven, Belgium Gabriele Kern-Isberner, Technical University of Dortmund, Germany Gerhard Lakemeyer, RWTH Aachen University, Germany PROGRAM COMMITTEE Franz Baader, TU Dresden, Germany Vaishak Belle, University of Edinburgh, UK Gerhard Brewka, University of Leipzig, Germany Guy Van den Broek, UCLA, USA Wolfram Burgard, University of Freiburg, Germany Esra Erdem, Sabanci University, Turkey Benjamin Kuipers, University of Michigan, USA Gabriele Kern-Isberner, Technical University of Dortmund, Germany Gerhard Lakemeyer, RWTH Aachen University, Germany Thomas Lukasiewicz, University of Oxford, UK Thomas Meyer, University of Cape Town, South Africa Bernhard Nebel, University of Freiburg, Germany Ron Petrick, Edinburgh, UK Luc De Raedt, KU Leuven, Belgium Gavin Rens, University of Cape Town, South Africa Torsten Schaub, University of Potsdam, Germany Siddharth Srivastava, Arizona State University, USA Prasad Tadepalli, Oregon State University, USA SUBMISSION INSTRUCTIONS Papers must be at most seven (7) pages in length and formatted according to the AAAI formatting instructions. Reviewing will be single-blind, that is, author names should be included in the submissions. Papers must be submitted in PDF format only by the due date at the EasyChair submission site https://easychair.org/conferences/?conf=hrl2018 IMPORTANT DATES Submission deadline: 04 August 2018 *** new *** Paper notification: 08 September 2018 *** new *** Registration deadline: TBD. Workshop date: 28 October 2018. _______________________________________________ uai mailing list uai@ENGR.ORST.EDU https://secure.engr.oregonstate.edu/mailman/listinfo/uai