• Submission deadline: 28 May, 2021 UTC-12
  • Notification: 28 June, 2021


Knowledge Engineering for Planning and Scheduling

    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
    • 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 will be done via EasyChair at https://easychair.org/conferences/?conf=keps2021.

    Important Dates

    Paper Submission:
    March 26, 2021 (UTC-12 time zone)
    May 28, 2021 (UTC-12 time zone)
    Notification: June 28, 2021

    KEPS 2021 Tentative Schedule

    10 minutes allocated to each paper, plus 5 minutes discussion.

    August 5th, 2021 (Everything in GMT)
    10.00 - 10.15 Welcome
    10.15 - 11.45 Session 1
    • Online Learning of Action Models for PDDL Planning
    • A Natural Language Model for Generating PDDL
    • Reuniting the LOCM Family: An Alternative Method for Identifying Static Relationships
    • Learning Temporal Plan Preferences from Examples: An Empirical Study
    • Learning User-Interpretable Descriptions of Black-Box AI System Capabilities

    12.15 - 13.45 Session 2
    • A Sound (but Incomplete) Polynomial Translation from Discretised PDDL+ to Numeric Planning
    • E-PDDL: A Standardized Way of Defining Epistemic Planning Problems
    • Application of MBSE to model Hierarchical AI Planning problems in HDDL
    • Computing Multiple PDR Steps in a Single SAT Call and a PDR Comparison to Madagascar with Completeness Thresholds
    • Within Task Preference Elicitation in Net Benefit Planning
    • Improving the Comprehension of HTN Planning Domains by Means of Preconditions and Effects of Compound Tasks --- Preliminary Results

    August 6th, 2021 (Everything in GMT)
    10.00 - 11.30 Session 3
    • Knowledge Engineering for Planning and Scheduling in the Context of Ontological Engineering: An Application in Railway Rolling Stock Maintenance
    • The Power of Waiting in Social Laws
    • Plan Verbalisation for Robots Acting in Dynamic Environments
    • On the Challenges of on-the-fly Knowledge Acquisition for Automated Planning Applications
    • Sailing Towards an Expressive Scheduling Language for Europa Clipper
    • Concept Languages as Expert Input for Generalized Planning: Preliminary Results

    12.15 - 13.45 Session 4 and Closing
    • A Tool to Model Task Planning Domain for Human-Robot Collaboration
    • Romie: A Domain-Independent Tool for Computer-Aided Robust Operations Management
    • TempAMLSI : Temporal Action Model Learning based on Grammar Induction
    • Automated Planning and Robotics Simulation with PDSim
    • GPT3-to-plan: Extracting plans from text using GPT-3

    Video presentations

    All the presentations can be found here.

    List of Accepted Papers

    PC Members

    • Roman Barták, Charles University
    • Yaniel Carreno, Edinburgh Centre for Robotics
    • Amedeo Cesta, CNR - National Research Council of Italy
    • Susana Fernandez, Universidad Carlos III de Madrid
    • Mary Ellen Foster, University of Glasgow
    • Simone Fratini, European Space Agency - ESA/ESOC
    • Alan Lindsay, Heriot-Watt University
    • Lee Mccluskey, University of Huddersfield
    • Alvin Ng, Heriot-Watt University
    • Eva Onaindia, Universitat Politècnica de València
    • Andrea Orlandini, National Research Council of Italy (ISTC-CNR)
    • Simon Parkinson, University of Huddersfield
    • Francesco Percassi, University of Huddersfield
    • Patricia Riddle, The University of Auckland
    • Enrico Scala, Università' di Brescia
    • Alessandro Umbrico, National Research Council of Italy (CNR-ISTC)


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