The motivation for using hierarchical planning formalisms is
manifold. It ranges from an explicit and predefined guidance
of the plan generation process and the ability to represent
complex problem solving and behavior patterns to the option
of having different abstraction layers when communicating
with a human user or when planning co-operatively. The
best-known formalism in the field is Hierarchical Task
Network (HTN) planning. In addition, there are several other
hierarchical planning formalisms, e.g., hybrid planning
(incorporating aspects from POCL planning), Hierarchical
Goal Network (HGN) planning (incorporating a hierarchy on
goals), or formalisms that combine task hierarchies with
timeline planning (e.g. ANML). Hierarchies induce
fundamental differences from classical planning, creating
distinct computational properties and requiring separate
algorithms from non-hierarchical planners. Many of these
aspects of hierarchical planning are still unexplored. Thus,
we encourage any contribution, independent of the underlying
hierarchical planning formalism, and want to provide a forum
for researchers to discuss the various aspects of
Topics of interests include but are not limited to:
- Theoretical foundations, e.g., complexity results
Heuristics, search, and other solving techniques for plan
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
Like ICAPS (and just like in 2020), HPlan will be carried out via gather.town. This year, attendance isn't free. To register for the entire ICAPS conference (including all workshops), it's 50 USD for non-students and 20 USD for students.
The first parts (invited talk and teaser talks) will be via zoom, the poster sessions will be carried out via gather.town. See our schedule below for more details. The zoom link is provided within our workshop room (behind door 1), you obtain it by pressing 'x'.
Some further useful information on attendance and gather.town:
- How to log in?
- First, log into the ICAPS website
- Now you should see a button "Attending" on the top-right next to your name, which was previously the login button
- Clicking it will reveal a large "Go to Gather -->" button. Click it! :)
- Please use your full name for your Avatar.
- Please use the button "g" while walking to enable the ghost mode, thus preventing you from opening audio and video connections while just walking by other people. That way you can also walk through others, which is practical in crowded spaces.
- You will be able to find the posters from the names of the respective papers.
- If you meet other people in a private area, note that under the line of videos in gather.town there is a double-arrow pointing to the bottom. If you hit it you see all group members like you would in Zoom.
- As said above, in order to join a zoom session, you have to hit "x" within our HPlan workshop room, thus temporarily leaving gather.town and running zoom.
- Note that the people presenting a poster might also want to attend a poster, so it could be that some poster is temporarily unattended for some some short while — just like in real life!
- We've added a few tables (small private areas) near the entrance of the workshop room (see screenshot below), where you could go to continue discussions after a session in case time was too short. Note that one poster session is scheduled right after another, so continuing discussion over the designated time window would not be possible as that would interrupt the next presentation and discussion.
- Note that authors or even participants might want to share their screen, e.g., to share additional sources (presentations, the paper etc.) or to open a whiteboard to draw examples. To do this, click on the computer symbol in your 'console' in the middle and bottom of your screen -- cf. screenshot below. Note that multiple people can share their screens simultaneously! They are just offered as additional screens that people can click on. (Make sure not to share the wrong thing or forget about it so you don't accidentally show private data like web pages or emails, etc.)
- Need further help?
The formatting guidelines (author kit, etc.) are the same as
for ICAPS 2021. Like at the main conference, there will be a
high quality double-blind review process against the
standard ICAPS criteria of significance, soundness,
scholarship, clarity, and reproducibility. However,
submissions may be less evolved than at the main conference.
We have two categories:
- Technical research papers (short or long) and
- Challenge papers (short).
Technical research papers are 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
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 5, resp. 9, pages can be used for
the paper, e.g. to address the reviewers' comments.
If you are interested in presenting work that was accepted
or published at a conference or journal, please contact the
organizers. We will not include such a paper into our
proceedings, but we are happy to discuss options for
presenting such work.
- Paper submission:
12 May (Papers may be updated until 17 May, but they need to be submitted and complete until the 12th. The additional days are only intended for optional minor improvements.)
- Camera-ready paper submission:
- Publish list of accepted papers:
- Proceedings/papers online:
- HPlan Workshop: Friday, 6 August, 2021 (6 hours), see ICAPS schedule (day 5) for time zone selection! Some selected time zones:
- 5 am to 11 am in parts of USA (EST)
- 9 am to 3 pm at virtual ICAPS (GMT)
- 11 am to 5 pm in e.g., Germany (MEST)
- 7 pm to 1 am in e.g., Canberra, Sydney, Melbourne (AEST)
The reference timezone for all deadlines is UTC-12, i.e., AoE.
- Compiling HTN Plan Verification Problems into HTN Planning Problems
by Daniel Höller, Julia Wichlacz, Pascal Bercher, and Gregor Behnke
- On the Computational Complexity of Correction HTN Domain Models
by Songtuan Lin and Pascal Bercher
- The Complexity of Flexible FOND HTN Planning
by Dillon Chen and Pascal Bercher
- A Hierarchical Approach to Multi-Agent Path Finding
by Han Zhang, Mingze Yao, Ziang Liu, Jiaoyang Li, Lucas Terr, Shao-Hung Chan, T. K. Satish Kumar, and Sven Koenig
- Task and Situation Structures for Service Agent Planning (that's a long version of a paper that was simultaneously accepted at the International Conference on Case-Based Reasoning (ICCBR 2021)
by Hao Yang, Tavan Eftekhar, Chad Esselink, Yan Ding, and Shiqi Zhang
- Solving Hierarchical Auctions with HTN Planning
by Antoine Milot, Estelle Chauveau, Simon Lacroix, and Charles Lesire
- Correcting Hierarchical Plans by Action Deletion (that paper was simultaneously accepted at the International Conference on Principles of Knowledge Representation and Reasoning (KR 2021)
by Roman Barták, Simona Ondrčková, Gregor Behnke, and Pascal Bercher
- On the Verification of Totally-Ordered HTN Plans
by Roman Barták, Simona Ondrčková, Gregor Behnke, and Pascal Bercher
- Temporal Hierarchical Task Network Planning with Nested Multi-Vehicle Routing Problems - A Challenge to be Resolved
by Jane Jean Kiam, Pascal Bercher, and Axel Schulte
- Towards Robust Constraint Satisfaction in Hybrid Hierarchical Planning
by Tobias Schwartz, Michael Sioutis, and Diedrich Wolter
- Domain Analysis: A Preprocessing Method that Reduces the Size of the Search Tree in Hybrid Planning
by Michael Staud
- GTPyhop: A Hierarchical Goal+Task Planner Implemented in Python
by Dana Nau, Sunandita Patra, Mark Roberts, Yash Bansod, and Ruoxi Li
- Integrating Planning and Acting With a Re-Entrant HTN Planner
by Yash Bansod, Dana Nau, Sunandita Patra, and Mark Roberts
- Solving POMDPs online through HTN Planning and Monte Carlo Tree Search
by Robert P. Goldman
Entire workshop proceedings
You find most of the teaser talks for the papers in HPlan's YouTube channel
9:00-12:15, Plenum Session:
- 9:00-9:10: Gathering and Welcome Words
- 9:10-10:10: Invited Talk (live!) by Malik Ghallab (with 15 minutes Q&A)
- 10:10-10:15: 5 minute break
- 10:15-12:05: poster teaser tasks for all 14 papers. 5-10 minutes each, no questions.
- 12:05-10:15: 10 minute break
12:15-13:00, Poster Session 1: Complexities and Compilations
- (poster 01) Compiling HTN Plan Verification Problems into HTN Planning Problems
- (poster 02) On the Computational Complexity of Correction HTN Domain Models
- (poster 04) The Complexity of Flexible FOND HTN Planning
13:00-13:45, Poster Session 2: Applications
- (poster 01) A Hierarchical Approach to Multi-Agent Path Finding
- (poster 02) Task and Situation Structures for Service Agent Planning
- (poster 04) Solving Hierarchical Auctions with HTN Planning
13:45-14:30, Poster Session 3: Challenges and Plan Verification
- (poster 01) Correcting Hierarchical Plans by Action Deletion
- (poster 02) Temporal Hierarchical Task Network Planning with Nested Multi-Vehicle Routing Problems - A Challenge to be Resolved
- (poster 03) On the Verification of Totally-Ordered HTN Plans
- (poster 04) Towards Robust Constraint Satisfaction in Hybrid Hierarchical Planning
14:30-15:15, Poster Session 4: Solving Planning Problems
- (poster 01) Domain Analysis: A Preprocessing Method that Reduces the Size of the Search Tree in Hybrid Planning
- (poster 02) GTPyhop: A Hierarchical Goal+Task Planner Implemented in Python
- (poster 03) Integrating Planning and Acting With a Re-Entrant HTN Planner
- (poster 04) Solving POMDPs online through HTN Planning and Monte Carlo Tree Search
Where to find which poster?
The screenshot above shows the HPlan workshop room, where you find four poster stands: 01, 02, 03, and 04.
In the schedule above we've indicated at which poster stand each paper will be presented.
Malik Ghallab gives an invited talk (available on YouTube
Hierarchical Online Reasoning for the Integration of Planning and Acting
Hierarchization in planning has often been viewed mainly as a means for reducing the search complexity, to be paid for with additional domain modeling efforts. HTN planning, for example, has sometime been opposed to generative planning techniques, and referred to as a programming paradigm in planning. We pursue here a quite different motivation for hierarchization than tractable computations in a huge search space. Namely, we are interested in planning for the purpose of acting, and consider hierarchization as a central concept for the integration of reasoning on actions and performing them.
We have argued in  that the design of a cognitive actor has to rely on two interconnected principles: (i) hierarchically organized deliberation, and (ii) continual online planning and reasoning. Many challenging problems for such a design have been underlined in , several of which remain pending, while a few have progressed towards acceptable solutions. This talk will report on a line of work that illustrates such a progress.1 Initiated in [2, Chap. 3], the work was pursued through several algorithmic developments and trials, e.g., in [3, 5, 6]; it reached a comprehensive stage in . The talk will motivate the integrated planning and acting issues and present three technical components:
- A hierarchical task-oriented knowledge representation for expressing operational models of actions (how to do things), which relies on a collection of refinement methods describing alternative ways to handle tasks and react to events. A refinement method can be any complex algorithm, with subtasks to be refined recursively and nondeterministic primitive actions which query and change the world.
- A Refinement Acting Engine (RAE) which interacts with an execution platform and performs online reasoning for the achievement of tasks and reaction to events by following refinement methods adapted to the current dynamic context, and retrying alternative methods when needed. RAE chooses its refinement methods with the help of a online optimizing planner.
- A Monte Carlo Tree Search planner, called UPOM, which assesses the utility of possible methods and finds an approximately optimal one for RAE to pursue an ongoing activity. UPOM is a progressive deepening, receding-horizon anytime planner which relies on domain-dependent heuristics, learned from simulations and/or real-world interactions.
A few empirical results will be presented.2
Extensions of the approach for handling temporal issues as well as space and motion planning issues (to address the well known “Task and Motion Planning”
TAMP problems) will be briefly discussed, together with perspectives for learning refinement methods for operational models.
: A line of work in collaboration with my co-authors Dana Nau, Paolo Traverso, Sunandita Patra and James Mason.
: A “Demonstration of Refinement Acting, Planning and Learning System Using Operational Models”
will be presented at the ICAPS 2021 demonstration session
- Ghallab, M., Nau, D., and Traverso, P. (2014). The actor’s view of automated planning and acting: A position paper. Artificial Intelligence, 208:1–17.
- Ghallab, M., Nau, D., and Traverso, P. (2016). Automated Planning and Acting. Cambridge University Press.
- Patra, S., Ghallab, M., Nau, D., and Traverso, P. (2019). APE: An Acting and Planning Engine. Advances in Cognitive systems, 7:175–194.
- Patra, S., Mason, J., Ghallab, M., Nau, D., and Traverso, P. (2021). Deliberative acting, planning and learning with hierarchical operational models. Artificial Intelligence, 299:103523.
- Patra, S., Mason, J., Ghallab, M., Traverso, P., and Nau, D. (2020). Integrating Acting, Planning, and Learning in Hierarchical Operational Models. In International Conference on Automated Planning and Scheduling (ICAPS 2020), pages 1–10.
- Patra, S., Traverso, P., Ghallab, M., and Nau, D. (2019). Acting and planning using operational models. In AAAI Conference on Artificial Intelligence (AAAI 2019), pages 7691–7698.
Malik Ghallab, Directeur de recherche emeritus at CNRS
LAAS-CNRS, 7 Av. Colonel Roche, 31077 Toulouse, France
The research activity of Malik Ghallab is focused on
AI and Robotics. He contributed to topics such as
knowledge representation and reasoning, planning, and
learning of skills and models of behaviors. He
(co-)authored over 200 technical papers and several
books. He taught AI at a few universities in France
and abroad; he advised 32 PhDs. He was director of
several AI research programs in France, director of
LAAS-CNRS and CTO of INRIA. He chairs the Steering
Committee of ANITI, the interdisciplinary AI institute
of Toulouse. His is involved in initiatives regarding
socially responsible research in AI and computational
sciences. He is ECCAI Fellow, and Docteur Honoris
Causa of Linköping University, Sweden.
In 2020, the International Planning Competition (IPC) was
on Hierarchical Task Network Planning. Visit
for results, participating planners, planning benchmarks,
HPlan has a
YouTube channel, which hosts the recorded talks since HPlan 2020 as well
as the results presentation of IPC 2020.
We have a mailing list (via google groups) for
hierarchical planning with currently approx. 70
subscribers. The list is low traffic, moderated, and only
allows mails related to hierarchical planning! Interested?
Drop Pascal a mail.
Previous HPlan workshops
Previous workshops are available here:
Or simply http://hplanYYYY.hierarchical-task.net (with YYYY being the year)
- Ron Alford
- Roman Barták
- Gregor Behnke
- Pascal Bercher
- Arthur Bit-Monnot
- Dillon Chen
- Lavindra de'Silva
- Juan Fernández-Olivares
- Florian Geißer
- Alban Grastien
- Daniel Höller
- Jane Jean Kiam
- Ugur Kuter
- Songtuan Lin
- Mauricio Cecilio Magnaguagno
- Conny Olz
- Simona Ondrčková
- Sunandita Patra
- Felix Richter
- Dominik Schreiber
- Shirin Sohrabi
- David Speck
- Alvaro Torralba
- Julia Wichlacz
- Zhanhao Xiao