[robotics-worldwide] [meetings][CFP] KEPS 2021 -- Call for Papers -- Extended Deadline

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[robotics-worldwide] [meetings][CFP] KEPS 2021 -- Call for Papers -- Extended Deadline

Petrick, Ron
2021 Workshop on Knowledge Engineering for Planning and Scheduling (KEPS)

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EXTENDED Deadline: March 26, 2021 (UTC-12)
https://urldefense.com/v3/__https://icaps21.icaps-conference.org/workshops/KEPS/__;!!LIr3w8kk_Xxm!9RmwAhXuaEUwl1ijOlVaw6CSq78GU_d8KvqsrjBrrzPUjUd0xMiUcApC_x1XazOHcrapjJ5y$ 
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Despite the progress in automated planning and scheduling systems, these systems still need to be fed by carefully engineered domain and problem description and they need to be fine-tuned for particular domains and problems. Knowledge engineering for AI planning and scheduling deals with the acquisition, design, validation and maintenance of domain models, and the selection and optimization of appropriate machinery to work on them. These processes impact directly on the success of real-world planning and scheduling applications. The importance of knowledge engineering techniques is clearly demonstrated by a performance gap between domain-independent planners and planners exploiting domain dependent knowledge.

The workshop shall continue the tradition of several International Competitions on Knowledge Engineering for Planning and Scheduling (ICKEPS) and KEPS workshops. Rather than focusing only on software tools and domain encoding techniques---which are topics of ICKEPS---the workshop will cover all aspects of knowledge engineering for AI planning and scheduling.

We seek original papers ranging from experience reports to the description of new technology in the following areas:

  *   formulation of domains and problem descriptions
  *   methods and tools for the acquisition of domain knowledge
  *   pre- and post-processing techniques for planners and schedulers
  *   acquisition and refinement of control knowledge
  *   formal languages for domain description
  *   re-use of domain knowledge
  *   translators from other application-area-specific languages to solver-ready domain models (such as PDDL)
  *   formats for specification of heuristics, parameters and control knowledge for solvers
  *   import of domain knowledge from general ontologies
  *   ontologies for describing the capabilities of planners and schedulers
  *   automated reformulation of problems
  *   automated knowledge extraction processes
  *   domain model, problem and plan validation and verification
  *   visualization methods for domain models, search spaces and plans
  *   mapping domain properties and planning techniques
  *   plan representation and reuse
  *   knowledge engineering aspects of plan analysis

We are pleased to accept papers based on recent publications from other (non ICAPS) venues such as specialized conferences (AAMAS, ICRA, KR, ...), or general AI conferences (AAAI, IJCAI, ECAI, ...). This must be however clearly indicated in the submitted paper.

Submissions of papers being reviewed at other venues are welcome since this is a non archival venue and we will not require a transfer of copyright. If such papers are currently under blind review, please anonymize the submission.

Submission Instructions

Two types of papers can be submitted. Full technical papers with the length up to 8 pages + 1 for references, are standard research papers. Short papers with the length between 2 and 4 pages (+1 for references) describe either a particular application or focus on open challenges. All papers must be submitted in a PDF format and must conform to the AAAI style template. The submission is done via EasyChair at the following link:

https://urldefense.com/v3/__https://easychair.org/conferences/?conf=keps2021__;!!LIr3w8kk_Xxm!9RmwAhXuaEUwl1ijOlVaw6CSq78GU_d8KvqsrjBrrzPUjUd0xMiUcApC_x1XazOHclXEO0Jy$ 

Important Dates

  *   Paper submission deadline: March 26, 2021 (UTC-12 time zone)
  *   Notification: April 23, 2021
  *   Camera-ready paper submission: TBD

Organizers

  *   Lukas Chrpa, Czech Technical University
  *   Ron Petrick, Heriot-Watt University
  *   Mauro Vallati, University of Huddersfield
  *   Tiago Vaquero, NASA JPL

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