6 Search Results for "Magazzeni, Daniele"

Document
DOI: 10.4230/LIPIcs.CP.2024.12
Using Constraint Programming for Disjunctive Scheduling in Temporal AI Planning

Authors: Adam Francis Green, J. Christopher Beck, and Amanda Coles

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
We present a novel scheduling model that leverages Constraint Programming (CP) to enhance problem solving performance in Temporal Planning. Building on the established strategy of decomposing causal and temporal reasoning, our approach abstracts two common fact structures present in many Temporal Planning problems - Semaphores and Envelopes - and performs temporal reasoning in a CP-based scheduler. At each search node in a heuristic search for a temporal plan, we construct and solve a Constraint Satisfaction Problem (CSP) and integrate feedback from the CP-based scheduler to guide the causal planning search towards a solution. Through experimental analysis, we validate the impact of these advances, demonstrating a significant reduction in both the number of states searched and in search time alongside an increase in problem-solving coverage.
Cite as

Adam Francis Green, J. Christopher Beck, and Amanda Coles. Using Constraint Programming for Disjunctive Scheduling in Temporal AI Planning. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 12:1-12:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{francisgreen_et_al:LIPIcs.CP.2024.12,
  author =	{Francis Green, Adam and Beck, J. Christopher and Coles, Amanda},
  title =	{{Using Constraint Programming for Disjunctive Scheduling in Temporal AI Planning}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{12:1--12:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.12},
  URN =		{urn:nbn:de:0030-drops-206974},
  doi =		{10.4230/LIPIcs.CP.2024.12},
  annote =	{Keywords: AI Planning, Temporal-Numeric Planning, Constraint Programming, Scheduling}
}
Document
DOI: 10.4230/DagMan.10.1.1
Current and Future Challenges in Knowledge Representation and Reasoning (Dagstuhl Perspectives Workshop 22282)

Authors: James P. Delgrande, Birte Glimm, Thomas Meyer, Miroslaw Truszczynski, and Frank Wolter

Published in: Dagstuhl Manifestos, Volume 10, Issue 1 (2024)

Abstract
Knowledge Representation and Reasoning is a central, longstanding, and active area of Artificial Intelligence. Over the years it has evolved significantly; more recently it has been challenged and complemented by research in areas such as machine learning and reasoning under uncertainty. In July 2022,sser a Dagstuhl Perspectives workshop was held on Knowledge Representation and Reasoning. The goal of the workshop was to describe the state of the art in the field, including its relation with other areas, its shortcomings and strengths, together with recommendations for future progress. We developed this manifesto based on the presentations, panels, working groups, and discussions that took place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge Representation: its origins, goals, milestones, and current foci; its relation to other disciplines, especially to Artificial Intelligence; and on its challenges, along with key priorities for the next decade.
Cite as

James P. Delgrande, Birte Glimm, Thomas Meyer, Miroslaw Truszczynski, and Frank Wolter. Current and Future Challenges in Knowledge Representation and Reasoning (Dagstuhl Perspectives Workshop 22282). In Dagstuhl Manifestos, Volume 10, Issue 1, pp. 1-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{delgrande_et_al:DagMan.10.1.1,
  author =	{Delgrande, James P. and Glimm, Birte and Meyer, Thomas and Truszczynski, Miroslaw and Wolter, Frank},
  title =	{{Current and Future Challenges in Knowledge Representation and Reasoning (Dagstuhl Perspectives Workshop 22282)}},
  pages =	{1--61},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2024},
  volume =	{10},
  number =	{1},
  editor =	{Delgrande, James P. and Glimm, Birte and Meyer, Thomas and Truszczynski, Miroslaw and Wolter, Frank},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.10.1.1},
  URN =		{urn:nbn:de:0030-drops-201403},
  doi =		{10.4230/DagMan.10.1.1},
  annote =	{Keywords: Knowledge representation and reasoning, Applications of logics, Declarative representations, Formal logic}
}
Document
DOI: 10.4230/LIPIcs.TIME.2021.13
Efficient Anytime Computation and Execution of Decoupled Robustness Envelopes for Temporal Plans

Authors: Michael Cashmore, Alessandro Cimatti, Daniele Magazzeni, Andrea Micheli, and Parisa Zehtabi

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)

Abstract
One of the major limitations for the employment of model-based planning and scheduling in practical applications is the need of costly re-planning when an incongruence between the observed reality and the formal model is encountered during execution. Robustness Envelopes characterize the set of possible contingencies that a plan is able to address without re-planning, but their exact computation is expensive; furthermore, general robustness envelopes are not amenable for efficient execution. In this paper, we present a novel, anytime algorithm to approximate Robustness Envelopes, making them scalable and executable. This is proven by an experimental analysis showing the efficiency of the algorithm, and by a concrete case study where the execution of robustness envelopes significantly reduces the number of re-plannings.
Cite as

Michael Cashmore, Alessandro Cimatti, Daniele Magazzeni, Andrea Micheli, and Parisa Zehtabi. Efficient Anytime Computation and Execution of Decoupled Robustness Envelopes for Temporal Plans. In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 13:1-13:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{cashmore_et_al:LIPIcs.TIME.2021.13,
  author =	{Cashmore, Michael and Cimatti, Alessandro and Magazzeni, Daniele and Micheli, Andrea and Zehtabi, Parisa},
  title =	{{Efficient Anytime Computation and Execution of Decoupled Robustness Envelopes for Temporal Plans}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{13:1--13:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.13},
  URN =		{urn:nbn:de:0030-drops-147895},
  doi =		{10.4230/LIPIcs.TIME.2021.13},
  annote =	{Keywords: Temporal Planning, Robustness Envelopes}
}
Document
DOI: 10.4230/DagRep.8.2.26
Planning and Operations Research (Dagstuhl Seminar 18071)

Authors: J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, and Willem-Jan Van Hoeve

Published in: Dagstuhl Reports, Volume 8, Issue 2 (2018)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 18071 "Planning and Operations Research". The seminar brought together researchers in the areas of Artificial Intelligence (AI) Planning, Constraint Programming, and Operations Research. All three areas have in common that they deal with complex systems where a huge space of interacting options makes it almost impossible to humans to take optimal or even good decisions. From a historical perspective, operations research stems from the application of mathematical methods to (mostly) industrial applications while planning and constraint programming emerged as subfields of artificial intelligence where the emphasis was traditionally more on symbolic and logical search techniques for the intelligent selection and sequencing of actions to achieve a set of goals. Therefore operations research often focuses on the allocation of scarce resources such as transportation capacity, machine availability, production materials, or money, while planning focuses on the right choice of actions from a large space of possibilities. While this difference results in problems in different complexity classes, it is often possible to cast the same problem as an OR, CP, or planning problem. In this seminar, we investigated the commonalities and the overlap between the different areas to learn from each other's expertise, bring the communities closer together, and transfer knowledge about solution techniques that can be applied in all areas.
Cite as

J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, and Willem-Jan Van Hoeve. Planning and Operations Research (Dagstuhl Seminar 18071). In Dagstuhl Reports, Volume 8, Issue 2, pp. 26-63, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{beck_et_al:DagRep.8.2.26,
  author =	{Beck, J. Christopher and Magazzeni, Daniele and R\"{o}ger, Gabriele and Van Hoeve, Willem-Jan},
  title =	{{Planning and Operations Research (Dagstuhl Seminar 18071)}},
  pages =	{26--63},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{8},
  number =	{2},
  editor =	{Beck, J. Christopher and Magazzeni, Daniele and R\"{o}ger, Gabriele and Van Hoeve, Willem-Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.8.2.26},
  URN =		{urn:nbn:de:0030-drops-92894},
  doi =		{10.4230/DagRep.8.2.26},
  annote =	{Keywords: Artificial Intelligence, Automated Planning and Scheduling, Constraint Programming, Dynamic Programming, Heuristic Search, Mixed Integer Programming, Operations Research, Optimization, Real-world Applications, Reasoning under Uncertainty}
}
Document
DOI: 10.4230/DagRep.7.1.32
Planning and Robotics (Dagstuhl Seminar 17031)

Authors: Malik Ghallab, Nick Hawes, Daniele Magazzeni, Brian C. Williams, and Andrea Orlandini

Published in: Dagstuhl Reports, Volume 7, Issue 1 (2017)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17031 on "Planning and Robotics". The seminar was concerned with the synergy between the research areas of Automated Planning & Scheduling and Robotics. The motivation for this seminar was to bring together researchers from the two communities and people from the Industry in order to foster a broader interest in the integration of planning and deliberation approaches to sensory-motor functions in robotics. The first part of the seminar was dedicated to eight sessions composed on several topics in which attendees had the opportunity to present position statements. Then, the second part was composed by six panel sessions where attendees had the opportunity to further discuss the position statements and issues raised in previous sessions. The main outcomes were a greater common understanding of planning and robotics issues and challenges, and a greater appreciation of crossover between different perspectives, i.e., spanning from low level control to high-level cognitive approaches for autonomous robots. Different application domains were also discussed in which the deployment of planning and robotics methodologies and technologies constitute an added value.
Cite as

Malik Ghallab, Nick Hawes, Daniele Magazzeni, Brian C. Williams, and Andrea Orlandini. Planning and Robotics (Dagstuhl Seminar 17031). In Dagstuhl Reports, Volume 7, Issue 1, pp. 32-73, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{ghallab_et_al:DagRep.7.1.32,
  author =	{Ghallab, Malik and Hawes, Nick and Magazzeni, Daniele and Williams, Brian C. and Orlandini, Andrea},
  title =	{{Planning and Robotics (Dagstuhl Seminar 17031)}},
  pages =	{32--73},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{7},
  number =	{1},
  editor =	{Ghallab, Malik and Hawes, Nick and Magazzeni, Daniele and Williams, Brian C. and Orlandini, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.7.1.32},
  URN =		{urn:nbn:de:0030-drops-72451},
  doi =		{10.4230/DagRep.7.1.32},
  annote =	{Keywords: adjustable autonomy, artificial intelligence, automated planning and scheduling, goal reasoning, human-robot interaction, plan execution, robotics}
}
Document
DOI: 10.4230/DagRep.4.11.227
Automated Planning and Model Checking (Dagstuhl Seminar 14482)

Authors: Alessandro Cimatti, Stefan Edelkamp, Maria Fox, Daniele Magazzeni, and Erion Plaku

Published in: Dagstuhl Reports, Volume 4, Issue 11 (2015)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 14482 "Automated Planning and Model Checking". There has been a lot of work on the exchanges between the areas of automated planning and model checking, based on the observation that a model-checking problem can be cast as a planning problem and vice-versa. The motivation for this seminar was to increase the synergy between the two research communities, and explore recent progress in the two areas in terms of techniques, tools and formalisms for describing planning and verification problems. The main outcomes were a greater common understanding of planning and model-checking issues and challenges, and greater appreciation of the crosswover between the modelling languages and methods. Different application domains were also explored, where planning and model-checking can be effectively integrated.
Cite as

Alessandro Cimatti, Stefan Edelkamp, Maria Fox, Daniele Magazzeni, and Erion Plaku. Automated Planning and Model Checking (Dagstuhl Seminar 14482). In Dagstuhl Reports, Volume 4, Issue 11, pp. 227-245, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@Article{cimatti_et_al:DagRep.4.11.227,
  author =	{Cimatti, Alessandro and Edelkamp, Stefan and Fox, Maria and Magazzeni, Daniele and Plaku, Erion},
  title =	{{Automated Planning and Model Checking (Dagstuhl Seminar 14482)}},
  pages =	{227--245},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{4},
  number =	{11},
  editor =	{Cimatti, Alessandro and Edelkamp, Stefan and Fox, Maria and Magazzeni, Daniele and Plaku, Erion},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.11.227},
  URN =		{urn:nbn:de:0030-drops-49731},
  doi =		{10.4230/DagRep.4.11.227},
  annote =	{Keywords: planning via model checking, directed model checking, plan validation, falsification, GPU-based state space exploration, hybrid systems, heuristic sea}
}
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