Knowledge Engineering for Planning and Scheduling (KEPS 2024)

2024 Workshop on Knowledge Engineering for Planning and Scheduling
Banff, Canada
June 2-3, 2024

Aim and Scope of the Workshop

Despite the progress in automated planning and scheduling systems, these systems still need to be fed by carefully engineered domain and problem descriptions 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 will continue the tradition of several International Competitions on Knowledge Engineering for Planning and Scheduling (ICKEPS) and prior 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 of Interest

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 describing domains
  • Re-use of domain knowledge
  • Translators from other application area-specific languages to solver-ready domain models (such as PDDL)
  • Formats for the 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

Important Dates

  • Paper submission deadline: March 28, 2024 (UTC-12 time zone)
  • Notification: April 28, 2024
  • Camera-ready paper submission: May 10, 2024

The reference timezone for all deadlines is UTC-12. That is, as long as there is still some place anywhere in the world where the deadline has not yet passed, you are on time!

Submission Details

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 ICAPS 2024 author kit instructions for formatting.

The submission will be done via EasyChair

Policy on Previously Published Materials

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, …). Such submissions must be clearly indicated in the 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.

List of Accepted Papers


Workshop Schedule


Organising Committee

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

Program Committee

  • Luigi Bonassi, Università degli Studi di Brescia
  • Sandra Castellanos, Grenoble Computer Science Laboratory, Université Grenoble Alpes
  • Matteo Cardellini, Università degli Studi di Genova
  • Francesco Percassi, University of Huddersfield
  • Jeremy Frank, NASA
  • Sergio Jimenez Celorrio, Universitat Politècnica de València
  • Andrea Orlandini, CNR
  • Lee McCluskey, University of Huddersfield
  • Susana Fernandez, Universidad Carlos III de Madrid
  • Simon Parkinson, University of Huddersfield
  • David Smith,
  • Eva Onaindia, Universitat Politècnica de València
  • Alan Lindsay, Heriot-Watt University
  • Roman Barták, Charles University
  • Simone Fratini, European Space Agency - ESA/ESOC
  • Alessandro Umbrico, National Research Council of Italy (CNR-ISTC)
  • Alba Gragera, Universidad Carlos III de Madrid
  • Yaniel Carreno, BAE Systems Digital Intelligence & Edinburgh Centre for Robotics
  • Raquel Fuentetaja, Universidad Carlos III de Madrid