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
-
A Sound (but Incomplete) Polynomial Translation
from Discretised PDDL+ to Numeric Planning
Francesco Percassi, Enrico Scala and Mauro Vallati
-
Learning Temporal Plan Preferences from Examples: An
Empirical Study
Valentin Seimetz, Rebecca Eifler and Joerg Hoffmann
-
E-PDDL: A Standardized Way of Defining Epistemic
Planning Problems
Francesco Fabiano, Biplav Srivastava, Jonathan Lenchner,
Lior Horesh, Francesca Rossi and Marianna Bergamaschi
Ganapini
-
On the Challenges of on-the-fly Knowledge Acquisition
for Automated Planning Applications
Saumya Bhatnagar, Sumit Mund, Enrico Scala, Keith McCabe,
Lee Mccluskey and Mauro Vallati
-
TempAMLSI : Temporal Action Model Learning based on
Grammar Induction
Maxence Grand, Damien Pellier and Humbert Fiorino
-
Application of MBSE to model Hierarchical AI Planning
problems in HDDL
Jasmine Rimani, Charles Lesire, Stéphanie Lizy-Destrez and
Nicole Viola
-
A Natural Language Model for Generating PDDL
Nisha Simon and Christian Muise
-
GPT3-to-plan: Extracting plans from text using GPT-3
Alberto Olmo, Sarath Sreedharan and Subbarao Kambhampati
-
Computing Multiple PDR Steps in a Single SAT Call and
a PDR Comparison to Madagascar with Completeness
Thresholds
Marshall Clifton and Charles Gretton
-
Online Learning of Action Models for PDDL Planning
Leonardo Lamanna, Alessandro Saetti, Luciano Serafini,
Alfonso Emilio Gerevini and Paolo Traverso
-
Within Task Preference Elicitation in Net Benefit
Planning
Alan Lindsay, Bart Craenen and Ron Petrick
-
Reuniting the LOCM Family: An Alternative Method for
Identifying Static Relationships
Alan Lindsay
-
A Tool to Model Task Planning Domain for Human-Robot
Collaboration
Elisa Foderaro, Amedeo Cesta, Alessandro Umbrico and
Andrea Orlandini
-
The Power of Waiting in Social Laws
Alexander Tuisov, Alexander Shleyfman and Erez Karpas
-
Plan Verbalisation for Robots Acting in Dynamic
Environments
Konstantinos Gavriilidis, Yaniel Carreno, Andrea Munafo,
Wei Pang, Ron Petrick and Helen Hastie
-
Sailing Towards an Expressive Scheduling Language for
Europa Clipper
Adrien Maillard, Marijke Jorritsma and Steve Schaffer
-
Concept Languages as Expert Input for Generalized
Planning: Preliminary Results
Rik de Graaff, Augusto B. Corrêa and Florian Pommerening
-
Towards Improving the Comprehension of HTN Planning Domains by Means of Preconditions and Effects of Compound Tasks
Conny Olz, Eva Wierzba, Pascal Bercher and Felix Lindner
-
Learning User-Interpretable Descriptions of Black-Box
AI System Capabilities
Pulkit Verma, Shashank Rao Marpally and Siddharth
Srivastava
-
Automated Planning and Robotics Simulation with PDSim
Emanuele De Pellegrin and Ronald Petrick
-
Knowledge Engineering for Planning and Scheduling in
the Context of Ontological Engineering: An Application
in Railway Rolling Stock Maintenance
Thomas Leo Mccluskey, Hassna Louadah, Emmanuel Papadakis,
Gareth Tucker, Adam Bevan and Peter Hughes
-
Romie: A Domain-Independent Tool for Computer-Aided
Robust Operations Management
Michael Saint-Guillain, Jonas Gibaszek, Tiago Stegun
Vaquero and Steve Chien
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)
Organization
- Lukas Chrpa, Czech Technical University
- Ron Petrick, Heriot-Watt University
- Mauro Vallati, University of Huddersfield
- Tiago Vaquero, NASA JPL