MPP 2014 - Workshop on Models and Paradigms for Planning under Uncertainty: a Broad Perspective

Probabilistic planning research mainly focused on a subset of uncertainty models, e.g., probabilistic ones such as (partially observable) Markov Decision Processes, or set-based ones such as non-deterministic and conformant planning. However, many other frameworks for describing uncertainty have been studied in Artificial Intelligence in general (e.g., possibilities, fuzzy logics, imprecise probabilities, Dempster-Shafer’s belief function), and other communities confronted with real-world problems like risk management use these models in their decision-making systems. We believe a cross-pollination of research approaches and methodologies from these relevant, yet mostly distant, paradigms will be very beneficial for the ICAPS community, leading to new ideas for tackling realistic planning problems.
Objectives and Topics
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
Submission Procedure
Paper submission is 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. Final papers will be in the same format, keep them to at most 8+1 pages long (i.e., 8 pages of content and 1 extra page only for references).
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.
Tutorial
We propose to organize a 1.5-hour tutorial on various models for planning under uncertainty. The covered topic will be:
probabilistic planning (Andrey Kolobov)
non-deterministic planning (Ugur Kuter)
possibilistic planning (Florent Teichteil)
dealing with partial observability (Guy Shani)
Important Dates
Paper submission: February 20th, 2014
Notification of acceptance: March 20th, 2014
Camera-ready paper submission: March 28th, 2014
Workshop date: June 22nd or June 23rd (TBA), 2014
Workshop Program Chairs
Andrey Kolobov (MSR Redmond, USA), akolobov at microsoft dot com
Ugur Kuter (SIFT, USA), ukuter at sift dot net
Florent Teichteil-Königsbuch (ONERA, France), florent dot teichteil at onera dot fr
Program Committee (to be completed)
Alexandre Albore (ONERA, France)
Dan Bryce (SIFT, USA)
Malik Ghallab (LAAS, France)
Steven Schockaert (Cardiff University, UK)
Guy Shani (Ben-Gurion University of the Negev, Israel)