2nd ICAPS Workshop on Hierarchical Planning

Collocated with ICAPS 2019 in Berkeley, USA.

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 hierarchical planning.

Topics of interests include but are not limited to: The formatting guidelines (author kit, etc.) are the same as at ICAPS 2019. Authors may submit long papers (8 pages plus up to one page of references) or short papers (4 pages plus up to one page of references). In case of acceptance, the full 5, resp. 9, pages can be used for the paper, e.g. to address the reviewers' comments.

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.

Submission page:
ICAPS asked all workshops to try out Open Review this year. We wanted to try it out, but limit its typical features: The main idea is to allow open reviewing by publishing all reviews. We will, however, only publish reviews if all authors and reviewers of a paper consent. (That is, every reviewer and the authors can veto publishing the reviews.)

Submission page of Open Review
Dana Nau Hierarchical Refinement as a Generalization of HTN Planning

For several years, Dr. Nau and several of his colleagues have been developing a new formalism and algorithms for planning and acting, based on the idea of hierarchical refinement. In this talk, he'll discuss how hierarchical refinement works, describe the ways in which hierarchical refinement methods generalize HTN methods, and describe the new planning techniques that are needed in order to take advantage of their expressive power. (Slides)

The work described in this talk has been done in collaboration with Sunandita Patra (U. of Maryland), Malik Ghallab (LAAS-CNRS), Paolo Traverso (FBK), and James Mason (U. of Maryland).


Dana Nau
Computer Science Dept, and Institute for Systems Research
University of Maryland

Dr. Nau does research on both automated planning and game theory. Some of his best-known work includes the discovery of "pathological" game trees in which deeper lookahead produces worse decisions, the strategic planning algorithm used to win the 1997 world championship of computer bridge, the SHOP and SHOP2 algorithms for HTN planning, two graduate-level textbooks on automated planning and acting, and evolutionary game-theoretic studies of human behavioral norms. Dr. Nau has more than 300 refereed publications. He is an AAAI Fellow and an ACM Fellow. The workshop proceedings are now available for download. By clicking on the individual papers above, you'll be forwarded to the individual page by openReview, where you can download the individual papers, and, depending on the authors' and reviewers' choice, the original workshop submission plus reviews (every author could veto to publish the reviews altogether while every reviewer could choose to hide their individual review). Morning Session: Afternoon Session 1: Afternoon Session 2:
  • 16:00 -- 16:30 Learning Domain Structure in HGNs for Nondeterministic Planning (Morgan Fine-Morris)
  • 16:30 -- 17:00 Learning HTN Methods with Preference from HTN Planning Instances (Zhanhao Xiao)
  • 17:00 -- 17:30 Parsing-based Approaches for Verification and Recognition of Hierarchical Plans (Roman Barták)
  • 17:30 -- 18:00 More Succinct Grounding of HTN Planning Problems – Preliminary Results (Gregor Behnke)
  • Submission deadline: March 29 (anywhere in the world), 2019 extended!
  • Notification of acceptance: May 3, 2019
  • Camera-ready paper: June 5, 2019
We encourage the submission of papers that are, at the time of submission, currently under review at the IJCAI conference 2019. In case such a double submission gets both accepted at IJCAI and at the workshop, the camera-ready paper for the workshop might be the same as for IJCAI or a (new) extended abstract of this paper of at most two pages including references (authors' choice).
  • Ron Alford
  • Gregor Behnke
  • Pascal Bercher
  • Susanne Biundo
  • Rogelio E. Cardona-Rivera
  • Lavindra de Silva
  • Humbert Fiorino
  • Daniel Höller
  • Héctor Muñoz-Avila
  • Damien Pellier
  • Felix Richter
  • Vikas Shivashankar
  • Austin Tate