[agents] [meetings] CFP - Special session on Knowledge Representation and Reasoning in Robotics @ ICSR 2014

[Mohan Sridharan]

Special session on Knowledge Representation and Reasoning in Robotics
The International Conference on Social Robotics
October 27-29, 2014
Sydney, Australia



MOTIVATION:

Robots and agents deployed to interact and collaborate with humans in
homes, offices, and other domains, have to represent knowledge and reason
at both the sensorimotor level and the cognitive/semantic (or social)
level. This objective maps to the fundamental challenge of representing,
revising, and reasoning with qualitative and quantitative descriptions of
uncertainty and incomplete domain knowledge obtained from sensors, humans,
and other sources.  Although many algorithms and architectures have been
developed for knowledge representation and reasoning, the research
community is fragmented, making it difficult for researchers with
complementary expertise to collaborate with each other. For instance, the
rich body of research in logical reasoning paradigms and qualitative
representations supports commonsense reasoning, encodes semantics such that
they are accessible to humans, and provides smaller state spaces for
learning and reasoning.  However such representations may not support
probabilistic analysis, whereas a lot of information available to robots at
the sensorimotor level is represented probabilistically to quantitatively
model the uncertainty in sensor input processing and actuation.  On the
other hand, the sophisticated algorithms based on probabilistic graphical
models that support quantitative modeling of uncertainty, make it difficult
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.

This special session seeks to bring together researchers from these
disparate communities, fostering an open discussion to promote a deeper
understanding and appreciation of recent breakthroughs and tough challenges
in the individual communities. We will build on the workshops that have
been organized on this theme, and on the broader theme of bringing AI and
robotics closer together. We hope that this special session will encourage
collaborative efforts towards addressing the knowledge representation and
reasoning challenges faced by robots interacting and collaborating with
humans.


TOPICS:

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.
* Planning and Robotics.
* Commonsense reasoning.
* Cognitive architectures.

We are especially interested in papers describing efforts to integrate
different approaches for knowledge representation, reasoning and/or
learning on robots and agents. We also encourage papers that clearly
identify the need for such an integration in different application domains
such as health care, search and rescue, surveillance, and smart homes.


FORMAT & SUBMISSIONS:

Papers submitted to this special session must follow the author guidelines
for ICSR. Please select the appropriate special session
during paper submission.

For more information, please see:
http://icsr2014.org/special-session.html


Paper submission: June 18, 2014
Notification: July 16, 2014


CHAIRS:

Mohan Sridharan, Texas Tech University
Subramanian Ramamoorthy, The University of Edinburgh
Vaishak Belle, University of Toronto

-----------------------------------------------------------------------


--Mohan Sridharan
http://www.cs.ttu.edu/~smohan