Eighth ICAPS Workshop on Hierarchical Planning (HPlan 2025)

Topics of interests include but are not limited to:

  • theoretical foundations, e.g., complexity results
  • heuristics, search, and other solving techniques for plan generation
  • techniques and foundations for providing modeling support
  • challenges and lessons learned from modeling systems (using hierarchical models)
  • applications of hierarchical planning
  • plan explanation for hierarchical models
  • hierarchical plan repair techniques
  • techniques for verifying solutions of hierarchical planning problems
  • techniques for automated learning and synthesis of hierarchical models
  • using Generative AI (like, e.g., LLMs) for hierarchical planning or modeling

Important Dates (updated!)

  • Submission Deadline: July 11 (Friday), 2025
  • Author Notification: August 15 (Friday), 2025
  • Camera-Ready Deadline: September 26 (Friday), 2025
  • ICAPS 2025 Workshops: Monday, November 10, 2025 (8:30 am - 12:00 pm)

Invited Talk

Roman Bartak

From Validation to Correction: Towards Autonomous Agents Based on Hierarchical Planning

Hierarchical plan validation gets a sequence of actions and determines if it is a valid hierarchical plan, that is, it is executable and can be obtained by decomposing some task. If the plan is valid, then a proof in the form of the task decomposition structure can be released. However, if the plan is not valid, plan validators simply state this. This is where plan correction may help by suggesting modifications to invalid plans, such as inserting or deleting actions, to make them valid hierarchical plans. Although the original motivation for plan correction was to enhance plan validation, the concept proved to apply to various other problems, including plan recognition, plan repair, and even planning itself.

The talk illustrates a journey from plan validation to plan correction, advocating plan correction as a general concept that encompasses various hierarchical planning tasks. As a future research direction, it suggests that a similar approach can be applied to planning domain models to obtain truly autonomous planning agents capable of learning and maintaining models of own behavior.

Roman Barták is a professor of computer science at Charles University, Prague. He works in the area of Artificial Intelligence with particular emphasis on automated planning and scheduling, constraint satisfaction, and knowledge representation. His research goal is to design intelligent autonomous agents (e.g. robots) that can plan their activities, do decisions, and act in real environment. He put strong emphasis on model-based approaches to problem-solving as a means to achieve trustworthy and explainable AI. Recently, his research has focused on two areas: multi-agent path finding and hierarchical planning.


Program

The workshop takes place on Monday morning, November 10th, from 8:30 am to 12:00 pm.

  •   8:30 –   9:30       Invited Talk by Roman Bartak
  •   9:30 –   10:00     Poster teaser talks, 3–4 minutes each:
    • David Chan: Hierarchical Goal Networks for Probabilistic Planning: Preliminary Results
    • Michael Staud A Formal Analysis of Hierarchical Planning with Multi-Level Abstraction
    • Israel Puerta-Merino: Towards a General Framework for HTN Modeling with LLMs
    • Pascal Lauer: PSPACE Planning With Expressivity Beyond STRIPS: Plan Constraints via Unordered HTNs, ILPs, Numerical Goals, and More
    • Roman Bartak: Parsing-based Planner for Totally Ordered HTN Planning with Task Insertion
    • Daniel Hoeller, from PRL workshop: Learning Heuristic Functions for HTN Planning
  • 10:00 – 10:30       coffee break! :)
  • 10:30 – 12:00       poster session for the above six talks/papers

Accepted Papers

We give our authors a short period after the conference (one to two weeks) to make updated to their papers in case they receive helpful feedback during the poster session/conference. We hence publish the entire proceedings after that time window. Note that we include page numbers due to these proceedings, but like in all years, all papers are non-archival.

Accepted at HPlan and included in proceedings


Accepted at HPlan and another venue

The following publication is excluded from the proceedings to prevent copyright issues. We will provide a link instead.


Presentations of papers from other venues

The following previously published papers are presented in the program but were not submitted to HPlan. (See “Policy on Previously Published Material”, where we offer to give you a forum to present work that was accepted at another venue already.)


Workshop Committee

  • Ron Alford, MITRE
  • Gregor Behnke, University of Amsterdam
  • Pascal Bercher, the Australian National University (ANU)
  • Maurice Dekker, University of Amsterdam
  • Humbert Fiorino, Université Grenoble Alpes (UGA)
  • Birte Glimm, Ulm University
  • Daniel Höller, Saarland University
  • Ugur Kuter, Smart Information Flow Technologies (SIFT)
  • Alexander Lodemann, Ulm University
  • Mario Schmautz, independent researcher
  • Mauro Vallati, University of Huddersfield
  • Michael Welt, Ulm University
  • Mohammad Yousefi, the Australian National University (ANU)
  • Yifan Zhang, the Australian National University (ANU)

Organizing Committee

Further Information

  • Are you interested in presenting your already published work? Reach out to us! (Also for next years!)
  • Do you want to join our team of reviewers? (Maybe even next year?) Please reach out to us!
  • On the HPlan website hplan.hierarchical-task.net you find, among others, a list of bibtex entries for all accepted papers in all HPlan editions. Individual workshop pages of past editions are available by adding the respective year, e.g., you may use hplan2024.hierarchical-task.net for last year’s edition (or hplan2025.hierarchical-task.net for this exact page).
  • We have a mailing list (via google groups) for hierarchical planning with currently approx. 70 subscribers. The list is almost zero traffic (in some years it is literally zero), moderated, and only allows mails related to hierarchical planning! Interested? Drop Pascal an email.

Information likely not relevant anymore

Submission Details

The formatting guidelines (author kit, etc.) are the same as for ICAPS 2025. There will be a high quality double-blind review process against the standard criteria of significance, soundness, scholarship, clarity, and reproducibility. However, submissions may be less evolved than at the main conference.

We have two categories:

  1. Technical research papers (short or long) and
  2. Challenge papers (short).

Technical research papers are like standard conference papers, but may be less evolved. The purpose of challenge papers is to report on or to make aware of interesting/important problems in Hierarchical Planning and to encourage discussion at the workshop – not to present some significant contribution.

Authors may submit long papers (up to 8 pages plus up to one page of references) or short papers (up to 4 pages plus up to one page of references). The purpose of short papers is to encourage publications of more preliminary results; challenge papers need to be short papers. In case of acceptance, the full 9, resp. 5, pages can be used for the paper.

Submissions will be done via easychair. The system doesn’t allow submissions yet, we are likely going to open it early June.

As written above, we are happy to check whether we can arrange an earlier submission, review, and notification date to accommodate your travel plans if required (e.g., for Visa). In this case we have to see how submissions will be done. Either way, contact the organizers at your earliest convenience in case you require this.

Double Submissions

We encourage the submission of papers that, at the time of submission, are under review at another conference (including JELIA, ECAI, and KR, for example). However, if the paper is also accepted at the respective conference, it will not be included in our proceedings. The paper will be included into the program, but the proceedings will only contain a link to the respective conference’s version.