*** WORKSHOP ANNOUNCEMENT ***
[Apologies for cross-posting]
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CALL FOR PAPERS
Workshop on Models and Paradigms for Planning Under Uncertainty
at the International Conference on Automated Planning and Scheduling
(ICAPS-2014)
Portsmouth, New Hampshire, USA, June 22nd or 23rd, 2014
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Great strides have been made in automated AI planning under uncertainty in
recent years, including symbolic and compact representations of planning
problems and very efficient techniques for solving them. The effectiveness of
these methods has been demonstrated in the past International Planning
Competitions, and, to some extent, in real-world applications such as
navigation tasks, space operations, railway control, and rescue/evacuation
tasks.
However, there are several remaining challenges for developing uncertainty
models for the planning systems. When deployed in the real world, these systems
often face a constantly changing environment, whose evolution is not
deterministic. In addition to the environmental dynamics, planning systems must
also deal with the partial knowledge about their surroundings, their models of
the environment, and their goals in that environment. Addressing all these
aspects successfully may require a range of modeling tools from precise and
imprecise probabilities to fuzzy and possibilistic logic.
The aim of this workshop is to discuss various models and paradigms for
planning under uncertainty in a broad sense, including but also going beyond
the traditional probabilistic planning paradigms.
Relevant topics include but are not limited to:
probabilistic or possibilistic (partially observable) Markov Decision Processes
non-probabilistic uncertainty models for planning and algorithms
conformant planning
imprecise probability models and planning
fuzzy and possibilistic logic
planning/replanning with deterministic planners
determinization-based approaches
modeling imperfect actuators and/or sensors and controller synthesis
belief-desire-intention (BDI) models, Dempster-Shafer theory
default reasoning and belief revision models
qualitative uncertainty models (e.g., Qualitative-Process (QP) theory,
qualitative probability models)
learning uncertainty models for planning
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Submission Procedure:
==================
Paper submissions are accepted in PDF only. Please format submissions in AAAI
style. Refer to the author instructions on the AAAI web site for detailed
formatting instructions and LaTeX style files. Papers can be submitted in one
of two categories:
Full papers: 8+1 pages long (i.e., 8 pages of content and 1 extra page only for
references)
Short papers: 4+1 pages long
Papers must be submitted by February 20th, 2014. All ICAPS deadlines refer to
23:59 in the UTC-12 time zone (i.e., if the deadline has not yet passed at some
place in the world, you are on time.)
Paper submissions should be made through the workshop EasyChair web site
https://www.easychair.org/conferences/?conf=mppu14.
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Important Dates:
=============
Papers Submission: February 20th, 2014
Notifications of acceptance: March 20th, 2014
Camera-Ready Paper Submissions: March 28th, 2014
Workshop Date: June 22nd or 23rd, 2014
=========
Organizers:
=========
Andrey Kolobov (MSR Redmond, USA)
Ugur Kuter (SIFT, USA)
Florent Teichteil-Königsbuch (ONERA, France)
================
Program Committee:
================
Alexandre Albore (ONERA, France)
Dan Bryce (SIFT, USA)
Jürgen Dix (Technical University of Clausthal, Germany)
Malik Ghallab (LAAS-CNRS, France)
Andrey Kolobov (MSR Redmond, USA)
Ugur Kuter (SIFT, USA)
Steven Schockaert (Cardiff University, UK)
Guy Shani (Ben-Gurion University of the Negev, Israel)
Florent Teichteil-Königsbuch (ONERA, France)
Paolo Traverso (FBK-ICT, Italy)
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