Dates

  • March 13, 2017 - Submissions Due
  • April 7, 2017 - Notification
  • April 21, 2017 - Camera-ready Due
  • June 19-20, 2017 - Workshop Date

Workshops

KEPS

2017 Workshop on Knowledge Engineering for Planning and Scheduling

An ICAPS'17 Workshop
Pittsburgh, USA
19-20 June 2017

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.

Topics and Objectives

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.

Example of typical topics for submissions in this workshop are:

  • 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
  • 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

Submission Information

Two types of papers can be submitted. Full technical papers with the length up to 8 pages (plus one for references) are standard research papers. Short papers with the length between 2 and 4 pages describe either a particular application, or focus on open challenges. All papers should conform to the AAAI style template. The papers must be submitted in a PDF format via the EasyChair system. Submissions will be reviewed by at least two referees.

In order to encourage the submission of original papers to the workshops, the ICAPS council has announced an initiative to fast-track strong workshop papers from one year to the main track of the next ICAPS. Up to two papers will be recommended by the KEPS organisers. The ICAPS 2018 program chairs will have a look at these papers and the workshop reviews and invite the authors of these papers to resubmit them to the ICAPS 2018 main track.

Important Dates

  • Paper submission deadline: March 13, 2017 (UTC-12 timezone)
  • Notification: April 7, 2017
  • Camera-ready paper submission: April 21, 2017

Organising Committee

  • Lukas Chrpa, Czech Technical University & Charles University in Prague, Czech Republic
  • Mauro Vallati, University of Huddersfield, UK
  • Tiago Vaquero, MIT & CalTech, USA

Schedule

June 19: 9:00 a.m. - 17:30 p.m.

9.00-10.30Session 1
Classical Planning in Latent Space: From Unlabeled Images to PDDL (and back)
Masataro Asai and Alex Fukunaga
Attribute Grammars with Set Attributes and Global Constraints as a Unifying Framework for Planning Domain Models
Roman Barták and Adrien Maillard
A PDDL Representation for Contradance Composition
Richard Freedman and Shlomo Zilberstein
10:30Coffee Break
11.00-12.30Session 2 (am)
StoryFramer: From Input Stories to Output Planning Models
Thomas Hayton, Julie Porteous, Joao Ferreira, Alan Lindsay and Jonathan Read
Extracting Incomplete Planning Action Models from Unstructured Social Media Data to Support Decision Making
Lydia Manikonda, Shirin Sohrabi, Kartik Talamadupula, Biplav Srivastava and Subbarao Kambhampati
Planning-based Scenario Generation for Enterprise Risk Management
Shirin Sohrabi, Anton Riabov and Octavian Udrea
14.30-15.30Session 3 (pm)
Invited Talk: The Hitchhiker's Guide to PDDL Modeling
Christian Muise and Nir Lipovetzky
15:30-4:00Coffee Break
16.00-17.30Session 4 (pm)
Domain Model Acquisition with Missing Information and Noisy Data
Peter Gregory, Alan Lindsay and Julie Porteous
Integrating Modeling and Knowledge Representation for Combined Task, Resource and Path Planning in Robotics
Simone Fratini, Tiago Nogueira and Nicola Policella
Method Composition through Operator Pattern Identification
Maurício Cecílio Magnaguagno and Felipe Meneguzzi

Accepted Papers

Masataro Asai and Alex Fukunaga
Classical Planning in Latent Space: From Unlabeled Images to PDDL (and back)

Roman Barták and Adrien Maillard
Attribute Grammars with Set Attributes and Global Constraints as a Unifying Framework for Planning Domain Models

Lydia Manikonda, Shirin Sohrabi, Kartik Talamadupula Biplav Srivastava and Subbarao Kambhampati
Extracting Incomplete Planning Action Models from Unstructured Social Media Data to Support Decision Making

Thomas Hayton, Julie Porteous, Joao Ferreira, Alan Lindsay and Jonathon Read
StoryFramer: From Input Stories to Output Planning Models

Simone Fratini, Tiago Nogueira and Nicola Policella
Integrating Modeling and Knowledge Representation for Combined Task, Resource and Path Planning in Robotics

Shirin Sohrabi, Anton Riabov and Octavian Udrea
Planning-based Scenario Generation for Enterprise Risk Management

Maurício Cecílio Magnaguagno and Felipe Meneguzzi
Method Composition through Operator Pattern Identification

Peter Gregory, Alan Lindsay and Julie Porteous
Domain Model Acquisition with Missing Information and Noisy Data

Richard Freedman and Shlomo Zilberstein
A PDDL Representation for Contradance Composition

Proceedings

The proceedings for this workshop as a PDF.