[robotics-worldwide] [meetings] CFP: ICAPS 2015 Workshop on Planning and Learning

Hanna Kurniawati hannakur at gmail.com
Mon Feb 2 13:34:58 PST 2015


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Call for Papers
ICAPS Workshop on Planning and Learning
http://www.cs.bgu.ac.il/~icaps15/workshops/pal.html
Jerusalem, Israel, June 7th/8th 2015
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Learning and planning are two distinct capabilities required for an intelligent agent, but they are connected in many ways and it is often beneficial to consider them together.

Learning allows planning to be more easily applied to new domains by serving as a means for automatically acquiring knowledge required in planning. In traditional planning methods, knowledge about the models and the search guidance are often manually specified, and can be very difficult or time-consuming to obtain. Many recent works have addressed the knowledge acquisition bottleneck by learning models for planning and learning heuristics to guide planning.

The techniques in planning can be used for solving learning problems. For example, Bayesian reinforcement learning for MDPs can be formulated as a Partially Observable Markov Decision Process (POMDP), and thus can be solved using a POMDP solution algorithm. The problem of active learning can be formulated as a planning problem too. Some existing learning or planning algorithms, when viewed from the right perspective, also show interesting connections between learning and planning. For example, adaptive Monte Carlo planning can be seen as online learning of search guidance.

This workshop aims to provide a stimulating forum for researchers from both the learning community and the planning community to discuss recent advances, and potential developments on these exciting topics at the intersection of learning and planning. This workshop is the continuation of the lineage of four workshops on planning and learning in 2007, 2009, 2011, and 2013.

Submissions are invited for topics on, but not limited to:
- Multi-agent planning and learning
- Robust planning in uncertain (learned) models
- Adaptive Monte Carlo planning
- Learning search heuristics for planner guidance
- Model-based reinforcement learning
- Bayesian reinforcement learning
- Model representations for learning and planning
- Theoretical aspects of planning and learning
- Learning and planning competition
- Applications of planning and learning, including applications in robotics.


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Important Dates

Submission Deadline: February 20, 2015.
Notifications and Technical Program: March 20, 2015.
Workshop Date: June 7th or 8th, 2015


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Paper Submission Procedure

Paper should be submitted via the workshop EasyChair web site https://easychair.org/conferences/?conf=icapswpal2015. 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 (http://www.aaai.org/Publications/Author/author.php). Final papers will be in the same format, keep them to at most 8+1 pages long (meaning 8 pages plus 1 extra page containing only references). All submitted papers will be peer-reviewed, and low-quality or off-topic papers will not be accepted. 


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Organizers

Alan Fern, Oregon State University, USA
Hanna Kurniawati, University of Queensland, Australia
Scott Sanner, NICTA & Australian National University, Australia
Nan Ye, National University of Singapore, Singapore



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