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.
The workshop proceedings are available for download
here.
The workshop will take place in Room 242 on Thursday, July 11. All presentations are
given 20 minutes, including 5 minutes for questions.
09:00 | Session 1: Probabilistic, Temporal, and Online Planning |
| Opening Remarks |
| Width-Based Lookaheads Augmented with Base Policies for Stochastic Shortest Paths |
| Guiding MCTS with Generalized Policies for Probabilistic Planning |
| Beyond Cost-to-go Estimates in Situated Temporal Planning |
| Simultaneous Re-Planning and Plan Execution for Online Job Arrival |
10:30 | Coffee Break |
11:00 | Session 2: Classical Planning |
| Simplifying Automated Pattern Selection for Planning with Symbolic Pattern Databases |
| Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning |
| Merge-and-Shrink Task Reformulation for Classical Planning |
| Learning How to Ground a Plan - Partial Grounding in Classical Planning |
12:30 | Lunch Break |
14:00 | Session 3: Task Reformulations, Goal Recognition |
| A* Search and Bound-Sensitive Heuristics for Oversubscription Planning |
| Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents |
| Reshaping Diverse Planning: Let There Be Light! |
| Top-Quality: Finding Practically Useful Sets of Best Plans |
- Width-Based Lookaheads Augmented with Base Policies for Stochastic Shortest Paths
Stefan O'Toole, Miquel Ramirez, Nir Lipovetzky, Adrian Pearce
- Simplifying Automated Pattern Selection for Planning with Symbolic Pattern Databases
Ionut Moraru, Santiago Franco, Stefan Edelkamp, Moises Martinez
- Simultaneous Re-Planning and Plan Execution for Online Job Arrival
Ivan Gavran, Maximilian Fickert, Ivan Fedotov, Joerg Hoffmann, Rupak Majumdar
- Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning
Jendrik Seipp
- Guiding MCTS with Generalized Policies for Probabilistic Planning
William Shen, Felipe Trevizan, Sam Toyer, Sylvie Thiebaux, Lexing Xie
- Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents
Sarah Keren, Haifeng Xu, Kofi Kwapong, David Parkes, Barbara Grosz
- Merge-and-Shrink Task Reformulation for Classical Planning
Alvaro Torralba, Silvan Sievers
- Beyond Cost-to-go Estimates in Situated Temporal Planning
Andrew Coles, Shahaf S. Shperberg, Erez Karpas, Solomon Eyal Shimony, Wheeler Ruml
- Top-Quality: Finding Practically Useful Sets of Best Plans
Michael Katz, Shirin Sohrabi, Octavian Udrea
- A* Search and Bound-Sensitive Heuristics for Oversubscription Planning
Michael Katz, Emil Keyder
- Reshaping Diverse Planning: Let There Be Light!
Michael Katz, Shirin Sohrabi
- Learning How to Ground a Plan - Partial Grounding in Classical Planning
Daniel Gnad, Alvaro Torralba, Martin Dominguez, Carlos Areces, Facundo Bustos
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 11th 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:
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automatic derivation of heuristic estimators for domain-independent planning
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formal results showing equivalence or dominance between heuristics
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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
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, or applications of machine learning in heuristic search
(e.g. learning heuristics, adaptive search strategies, or heuristic selection).
We will keep this stance, particularly as ICAPS 2019 will continue the special
track on planning & learning.
Please format submissions in AAAI style (see instructions in the Author Kit at
https://www.aaai.org/Publications/Templates/AuthorKit19.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.
Submissions
will be made through OpenReview. The following conditions apply:
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Submissions will be double blind to the general public and to the reviewers.
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The submitted papers, reviews and author responses to those will be public, and all anonymous.
(since paper PDFs will be public, please remove all information that might reveal author identity to the public from the submitted PDF)
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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.
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).
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 to
alternative lines of research on the topic of choice.
At least one author of each accepted paper must attend the workshop in order to
present the paper. Authors must register for the ICAPS main conference in order
to attend the workshop. There will be no separate workshop-only registration.
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Submission deadline: 17 March 2019 (UTC-12 timezone)
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Notification: 12 April 2019
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Camera Ready: 24 May 2019
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Workshop: 11/12 July 2019
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Daniel Gnad, Saarland University, Germany, gnad at cs.uni-saarland.de
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Miquel Ramirez, University of Melbourne, Australia, miquel.ramirez at unimelb.edu.au
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Patrik Haslum, Australian National University, Australia
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Daniel Gnad, Saarland University, Germany
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Miquel Ramirez, University of Melbourne, Australia
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Florian Pommerening, University of Basel, Switzerland
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Jendrik Seipp, University of Basel, Switzerland
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Florian Geisser, Australian National University, Australia
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Guillem Francès, University of Basel, Switzerland
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Silvan Sievers, University of Basel, Switzerland