====================================================================== **DEADLINE EXTENSION to MAY 23 to avoid NIPS submission conflict**
CFP: ICML/IJCAI/AAMAS 2018 Workshop on *Planning and Learning* (PAL-18) https://sites.google.com/site/planlearn18/ Stockholm, Sweden July 14 or 15, 2018 ====================================================================== Planning and learning are both core areas of Artificial Intelligence. The reinforcement learning community has mostly relied on approximate dynamic programming and Monte-Carlo tree search as its workhorses for planning, while the field of planning has developed a diverse set of representational formalisms and scalable algorithms that are currently underexplored in learning approaches. Further, the planning community could benefit from the tools and algorithms developed by the machine learning community, for instance to automate the generation of planning problem descriptions. The purpose of this workshop is to encourage discussion and collaboration between the communities of planning and learning. Furthermore, we also expect that agents and general AI researchers are interested in the intersection of planning and learning, in particular those that focus on intelligent decision making. As such, the joint workshop program is an excellent opportunity to gather a large and diverse group of interested researchers. Workshop topics: ================ The Planning and Learning workshop solicits work at the intersection of the fields of machine learning and planning. We also solicit work solely in one area that can influence advances in the other so long as the connections are *clearly articulated* in the submission. 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 * Reinforcement learning (model-based, Bayesian, deep, etc.) * Model representation and learning for planning * Theoretical aspects of planning and learning * Learning and planning competition(s) * Applications of planning and learning Invited Speakers: ================= * Pieter Abbeel, UC Berkeley * Emma Brunskill, Stanford University * Craig Boutilier, Google (Mountain View) * Thore Graepel, Google DeepMind Important Dates: ================ * Submission deadline: Extended to May 23, 2018 (11:59pm Hawaii Time) * Notification date: May 30, 2018 * Camera-ready deadline: June 13, 2018 * Workshop date: July 14 or 15 (TBD), 2018 Submission Procedure: ===================== We solicit workshop paper submissions relevant to the above call of the following types: * Long papers -- up to 8 pages + unlimited references / appendices * Short papers -- up to 4 pages + unlimited references / appendices * Extended abstracts -- up to 2 pages + unlimited references / appendices We will accept papers in any of the IJCAI, ICML, AAMAS, or NIPS formats. Submissions are not anonymous and should include author information. Some accepted long papers will be accepted as contributed talks. All accepted long and short papers and extended abstracts will be given a slot in the poster presentation session. Extended abstracts are intended as brief summaries of already published papers, challenge or position papers, or preliminary work. Paper submissions should be made through EasyChair: https://easychair.org/conferences/?conf=pal18 Organizing Committee: ===================== Scott Sanner, University of Toronto Matthijs Spaan, TU Delft Timothy Mann, Google DeepMind Aviv Tamar, UC Berkeley
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