KRRR 2014 - Workshops on Knowledge Representation and Reasoning in Robotics

Robots and agents deployed in homes, offices and other complex domains are faced with the formidable challenge of representing, revising and reasoning with incomplete domain knowledge acquired from sensor inputs and human feedback. Although many algorithms have been developed for qualitatively or quantitatively representing and reasoning with knowledge, the research community is fragmented, with separate vocabularies that are increasingly making it difficult for these researchers to communicate with each other. For instance, the rich body of research in knowledge representation using logical reasoning paradigms provides appealing commonsense reasoning capabilities, but does not support probabilistic modeling of the considerable uncertainty in sensing and acting on robots. In parallel, robotics researchers are developing sophisticated probabilistic algorithms that elegantly model the uncertainty in sensing and acting on robots, but it is difficult to use such algorithms to represent and reason with commonsense knowledge. Furthermore, algorithms developed to combine logical and probabilistic reasoning do not provide the desired expressiveness for commonsense reasoning and/or do not fully support the uncertainty modeling capabilities required in robotics.
The objective of this symposium is to promote a deeper understanding of recent breakthroughs and challenges in the logical reasoning and probabilistic reasoning communities. We seek to encourage collaborative efforts towards building knowledge representation and reasoning architectures that support qualitative and quantitative descriptions of knowledge and uncertainty.
We are interested in efforts that integrate, or motivate an integration of, logic-based and probabilistic algorithms for knowledge representation and/or commonsense reasoning on one or more robots or agents in different application domains. Topics of interest include (but are not limited to):
Knowledge acquisition and representation.
Combining symbolic and probabilistic representations.
Reasoning about uncertainty.
Reasoning with incomplete knowledge.
Interactive and cooperative decision-making.
Learning and symbol grounding.
Commonsense reasoning.
We also encourage the submission of papers that ground these topics in research areas such as robot vision, human-robot (and multirobot) collaboration, and robot planning.
If your research is primarily in qualitative representations for robots, please consider submitting your paper to a parallel symposium: Qualitative Representations for Robots. If you are not sure which of the two symposia is the best venue for your paper, please send a joint email with a description of your work to the corresponding chair: Mohan Sridharan and Nick hawes.
Paper Submission
The workshop will consist of paper and poster presentations, invited talks, discussion sessions, and demos. Invited speakers will describe results of long-terms efforts focused on integrating knowledge representation, logical reasoning and/or probabilistic reasoning on robots and agents. Poster sessions and oral presentations will be determined after all paper submissions have been reviewed by at least two members of the program committee. Paper submissions can be in one of the following categories:
Regular paper: the length of regular papers (including figures and bibliography) should not exceed 8 pages.
Poster/summary paper: the length of poster/summary papers (including all figures and bibliography) should not exceed 4 pages.
Papers must be written using AAAI format. Submit your papers at the easychair web site for this symposium.
Committees
The organizing committee for this workshop:
Mohan Sridharan
Department of Computer Science
Texas Tech University
Lubbock, TX 79409, USA
mohan.sridharan-AT-ttu.edu
Fangkai Yang
Department of Computer Sciences
The University of Texas at Austin
Austin, TX 78712, USA
fkyang-AT-cs.utexas.edu
Subramanian Ramamoorthy
School of Informatics
The University of Edinburgh
Edinburgh EH8 9AB, UK
s.ramamoorthy-AT-ed.ac.uk
Volkan Patoglu
Mechatronics Program
Faculty of Engineering and Natural Sciences
Sabanci University, Istanbul, Turkey
vpatoglu-AT-sabanciuniv.edu
Esra Erdem
Computer Science Program
Faculty of Engineering and Natural Sciences
Sabanci University, Istanbul, Turkey
esraerdem-AT-sabanciuniv.edu
The program committee for this workshop:
Alfredo Gabaldon, Carnegie Mellon University, Silicon Valley.
Michael Gelfond, Texas Tech University.
Frank Guerin, University of Aberdeen.
Chad Jenkins, Brown University.
Jianmin Ji, University of Science and Technology of China.
Lars Karlsson, Orebro University.
Matteo Leonetti, The University of Texas at Austin.
Vladimir Lifschitz, The University of Texas at Austin.
Daniele Nardi, Sapienza University of Rome.
Maurice Pagnucco, University of New South Wales.
Ron Petrick, University of Edinburgh.
Orkunt Sabuncu, University of Potsdam.
Alessandro Saffioti, Orebro University.
Sanem Sariel-Talay, Istanbul Technical University.
Tran Cao Son, New Mexico State University.
Mary-Anne Williams, University of Technology, Sydney.
Shiqi Zhang, Texas Tech University.