• Submission deadline: 13 May, 2021 UTC-12
  • Notification: 10 June, 2021
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Heuristics and Search for Domain-independent Planning (HSDIP)

    Heuristics and search algorithms are the two key components of heuristic search, one of the main approaches to many variations of domain-independent planning, including classical planning, temporal planning, planning under uncertainty and adversarial planning. This workshop seeks to understand the underlying principles of current heuristics and search methods, their limitations, ways for overcoming those limitations, as well as the synergy between heuristics and search.

    Schedule - August 4

    Presentations are allocated 12 min per paper, plus 5 min discussion. Details about how to join the workshop will be posted soon.
    For some time zones, the workshop ends on August 5.

    Time
    {{showDayWithMin(HSDIP_DAY,7,00)}} Opening Remarks
    {{showDayWithMin(HSDIP_DAY,7,10)}} Keynote Shirin Sohrabi
    AI Planning: Challenges and Opportunities
    {{showDayWithMin(HSDIP_DAY,8,10)}} Break
    {{showDayWithMin(HSDIP_DAY,8,30)}} Session 1
    • A Branch-and-Cut Approach for a Mixed Integer Linear Programming Compilation of Optimal Numeric Planning
      Ryo Kuroiwa, Chris Beck
    • Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning
      Pascal Lauer, Álvaro Torralba, Daniel Fišer, Daniel Höller, Julia Wichlacz, Jörg Hoffmann
    • Custom-Design of FDR Encodings: The Case of Red-Black Planning
      Daniel Fišer, Daniel Gnad, Michael Katz, Jörg Hoffmann
    • A Compilation Based Approach to Finding Centroids and Minimum Covering States in Planning
      Erez Karpas
    • Classical Planning with Avoid Conditions
      Marcel Steinmetz, Jörg Hoffmann, Stefan Borgwardt, Alisa Kovtunova
    {{showDayWithMin(HSDIP_DAY,10,00)}} Break
    {{showDayWithMin(HSDIP_DAY,10,30)}} Session 2
    • Learning To Estimate Search Progress Using Sequence Of States
      Matan Sudry, Erez Karpas
    • Learning-based Synthesis of Social Laws in STRIPS
      Ronen Nir, Alexander Shleyfman, Erez Karpas
    • Metareasoning for Tuning the Hyperparameters of Anytime Planning: A Deep Reinforcement Learning Approach
      Abhinav Bhatia, Justin Svegliato, Shlomo Zilberstein
    • Efficient Black-Box Planning Using Macro-Actions with Focused Effects
      Cameron Allen, Michael Katz, Tim Klinger, George Konidaris, Matthew D Riemer, Gerald Tesauro
    • Cost Optimal Planning as Satisfiability
      Mohammad Abdulaziz
    {{showDayWithMin(HSDIP_DAY,12,00)}} Break
    {{showDayWithMin(HSDIP_DAY,13,00)}} Session 3
    • LM-BFS: A Framework for Landmarks in Planning
      Clemens Büchner, Thomas Keller
    • Introducing Operator-Potential Heuristics for Symbolic Search
      Daniel Fišer, Álvaro Torralba, Jörg Hoffmann
    • Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches
      Dominik Drexler, Jendrik Seipp, Hector Geffner
    • The Fewer the Merrier: Pruning Preferred Operators with Novelty
      Alexander Tuisov, Michael Katz
    • A*+BFHS: A Hybrid Heuristic Search Algorithm
      Zhaoxing Bu, Richard Korf
    {{showDayWithMin(HSDIP_DAY,14,30)}} Closing, Social Meeting, Discussions

    Keynote Speaker

    The HSDIP workshop is proud to announce that Shirin Sohrabi will give a keynote presentation on AI Planning: Challenges and Opportunities for this year’s workshop.

    Shirin Sohrabi is a research staff member and research manager at IBM T.J. Watson Research Center in Yorktown Heights, New York. Her research interests are in the area of Artificial Intelligence (AI) with a focus on AI planning and its many applications. In particular, she is interested in knowledge engineering and modeling issues for AI planning, planning with preferences, cost-sensitive planning, diverse planning, as well as combining AI planning and reinforcement learning. She has served as program co-chair of ICAPS 2020, as Novel Application Track co-chair of ICAPS 2018-2019, and as System Demonstration Track chair of AAAI 2018. She received the outstanding reviewer award at ICAPS-16. She regularly serves on the PC and SPCs of ICAPS, IJCAI and AAAI. She is an ACM senior member and a member of ICAPS executive council.

    Accepted Papers

    • Custom-Design of FDR Encodings: The Case of Red-Black Planning (Recording) (PDF)
      Daniel Fišer, Daniel Gnad, Michael Katz, Jörg Hoffmann
    • A Branch-and-Cut Approach for a Mixed Integer Linear Programming Compilation of Optimal Numeric Planning (Recording) (PDF)
      Ryo Kuroiwa, Chris Beck
    • LM-BFS: A Framework for Landmarks in Planning (Recording) (PDF)
      Clemens Büchner, Thomas Keller
    • Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning (Recording) (PDF)
      Pascal Lauer, Álvaro Torralba, Daniel Fišer, Daniel Höller, Julia Wichlacz, Jörg Hoffmann
    • A*+BFHS: A Hybrid Heuristic Search Algorithm (Recording) (PDF)
      Zhaoxing Bu, Richard Korf
    • Metareasoning for Tuning the Hyperparameters of Anytime Planning: A Deep Reinforcement Learning Approach (Recording) (PDF)
      Abhinav Bhatia, Justin Svegliato, Shlomo Zilberstein
    • Classical Planning with Avoid Conditions (Recording) (PDF)
      Marcel Steinmetz, Jörg Hoffmann, Stefan Borgwardt, Alisa Kovtunova
    • Introducing Operator-Potential Heuristics for Symbolic Search (Recording) (PDF)
      Daniel Fišer, Álvaro Torralba, Jörg Hoffmann
    • Learning-based Synthesis of Social Laws in STRIPS (Recording) (PDF)
      Ronen Nir, Alexander Shleyfman, Erez Karpas
    • A Compilation Based Approach to Finding Centroids and Minimum Covering States in Planning (Recording) (PDF)
      Erez Karpas
    • Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches (Recording) (PDF)
      Dominik Drexler, Jendrik Seipp, Hector Geffner
    • Efficient Black-Box Planning Using Macro-Actions with Focused Effects (Recording) (PDF)
      Cameron Allen, Michael Katz, Tim Klinger, George Konidaris, Matthew D Riemer, Gerald Tesauro
    • The Fewer the Merrier: Pruning Preferred Operators with Novelty (Recording) (PDF)
      Alexander Tuisov, Michael Katz
    • Cost Optimal Planning as Satisfiability (Recording) (PDF)
      Mohammad Abdulaziz
    • Learning To Estimate Search Progress Using Sequence Of States (Recording) (PDF)
      Matan Sudry, Erez Karpas

    Topics and Objectives

    Search guided by heuristics, automatically derived from a declarative formulation of action effects, preconditions and goals, has been a successful approach to domain-independent planning. From the initial success of heuristics based on syntactic relaxations and abstractions, the theory and practice of developing novel heuristics have become more diverse, often borrowing concepts and tools from Optimisation and Satisfiability, and bolder, tackling more expressive planning languages.

    In parallel to the increasing maturity of the methods and tools used to derive heuristic methods, important theoretical results have brought around a more clear image of how heuristic methods relate to each other. For instance, it has been shown that classic frameworks for heuristic search as planning can be encoded symbolically and their execution simulated via off-the-shelf satisfiability solvers. Groundbreaking theoretical work has shown how heuristic methods can be grouped into distinct families, depending on whether they can or cannot be shown to dominate or be compiled into each other.

    As a result, the formulation of heuristics for domain-independent planning is increasingly being less about describing procedures that exploit specific features in declarative information, and more about describing auxiliary constraints that make apparent those features to off-the-shelf solvers that operate over a logical or algebraic theory that over-approximate the set of valid plans and compute the heuristic estimator.

    Last, but not least, there is a growing realization that the search algorithm used can significantly amplify or reduce the utility of specific heuristics. Recent work that highlights the pitfalls latent in well-known search algorithms, also suggests opportunities to exploit synergies between the heuristic calculation and the search control.

    The workshop on Heuristics and Search for Domain-Independent Planning (HSDIP) is the 13th workshop in a series that started with the "Heuristics for Domain-Independent Planning" (HDIP) workshops at ICAPS 2007. At ICAPS 2012, the workshop was changed to its current name and scope to explicitly encourage work on search for domain-independent planning.

    Examples of typical topics for submissions to this workshop are:

    • automatic derivation of heuristic estimators for domain-independent planning
    • formal results showing equivalence or dominance between heuristics
    • novel heuristic methods dealing with planning with numeric variables and effects, partial observability and non-deterministic action effects
    • heuristic estimators for domain-independent planning via procedures or suitably defined encodings of declarative descriptions of planning tasks into Satisfiability or Optimisation
    • novel search techniques for domain-independent planning that explicitly aim at exploiting effectively the properties of existing heuristics
    • empirical observations of synergies between heuristics and search in domain-independent planning
    • challenging domains for existing combinations of heuristics and search algorithms
    • applications of machine learning in heuristic search, e.g., learning heuristics, adaptive search strategies, or heuristic selection.

    The HSDIP workshop has always been welcoming of multidisciplinary work, for example, drawing inspiration from operations research (like row and column generation algorithms), convex optimization (like gradient optimization for hybrid planning), constraint programming, or satisfiability.

    The workshop is meant to be an open and inclusive forum, and we encourage papers that report on work in progress or that do not fit the mold of a typical conference paper. Non-trivial negative results are welcome to the workshop, but we expect the authors to argue for the significance of the presented results.

    Deadlines and Dates

    Due to ICAPS being postponed we decided to extend the workshop deadline. We will announce a new deadline as soon as possible, submission will remain open.

    • Paper submission deadline:
      10 March 2021 (UTC-12 timezone)
      18 March 2021 (UTC-12 timezone)
      13 May 2021 (UTC-12 timezone)
    • Open Discussion: 27 May - 8 June 2021
    • Notification: 10 June 2021
    • Camera-ready paper submission: 19 July 2021
    • Workshop: August 4 (for some time zones it ends on August 5)

    Submissions

    Please format submissions in AAAI style (see instructions in the Author Kit at https://www.aaai.org/Publications/Templates/AuthorKit21.zip) and keep them to at most 9 pages including references. Authors considering submitting to the workshop papers rejected from the main conference, please ensure you do your utmost to address the comments given by ICAPS reviewers. Please do not submit papers that are already accepted for the main conference to the workshop.

    In addition to the submitted PDF paper, authors can submit supplementary material (videos, technical proofs, additional experimental results) for their paper. Please make sure that the supporting material is also anonymized. Papers should be self-contained; reviewers are encouraged, but not obligated, to consider supporting material in their decisions.

    Submissions will be made through OpenReview:

    https://openreview.net/group?id=icaps-conference.org/ICAPS/2021/Workshop/HSDIP

    The following conditions apply:

    • Submissions will be double blind in general and single blind to the area chair.
    • The submitted papers, reviews and discussion between authors and reviewers will be public, and all anonymous.
    • Discussions between reviewers and organisers will be private.

    Every submission will be reviewed by two members of the organizing committee according to the usual criteria such as relevance to the workshop, significance of the contribution, and technical quality. There will be a brief discussion phase where author and reviewers can interactively engage and discuss the submission and the reviews.

    Submissions sent to other conferences are allowed. It is the responsibility of the authors to ensure that those venues allow for papers submitted to be already published in "informal" ways (e.g. on proceedings or websites without associated ISSN/ISBN). In particular, we welcome submissions sent to the IJCAI conference and made sure that the workshop discussion phase does not conflict with the IJCAI rebuttal phase.

    At least one author of each accepted paper must attend the workshop in order to present the paper. The workshop format (fully virtual or hybrid) will be the same as the format of the main conference. Authors must register for the ICAPS conference in order to attend the workshop.

    Organization

    • Salomé Eriksson, University of Basel, Switzerland
    • Patrick Ferber, University of Basel, Switzerland
    • Daniel Fišer, Czech Technical University, Czech Republic, and Saarland University, Germany
    • Daniel Gnad, Saarland University, Germany
    • Florian Pommerening, University of Basel, Switzerland
    • David Speck, University of Freiburg, Germany
    • Álvaro Torralba, Aalborg University, Denmark

    Program Commitee

    • Augusto B. Corrêa
    • Salomé Eriksson
    • Patrick Ferber
    • Maximilian Fickert
    • Daniel Fišer
    • Florian Geißer
    • Daniel Gnad
    • Antonín Komenda
    • Christian Muise
    • Florian Pommerening
    • David Speck
    • Álvaro Torralba