3 Search Results for "Cashmore, Michael"

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/LIPIcs.TIME.2021.15
Olisipo: A Probabilistic Approach to the Adaptable Execution of Deterministic Temporal Plans

Authors: Tomás Ribeiro, Oscar Lima, Michael Cashmore, Andrea Micheli, and Rodrigo Ventura

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

Abstract
The robust execution of a temporal plan in a perturbed environment is a problem that remains to be solved. Perturbed environments, such as the real world, are non-deterministic and filled with uncertainty. Hence, the execution of a temporal plan presents several challenges and the employed solution often consists of replanning when the execution fails. In this paper, we propose a novel algorithm, named Olisipo, which aims to maximise the probability of a successful execution of a temporal plan in perturbed environments. To achieve this, a probabilistic model is used in the execution of the plan, instead of in the building of the plan. This approach enables Olisipo to dynamically adapt the plan to changes in the environment. In addition to this, the execution of the plan is also adapted to the probability of successfully executing each action. Olisipo was compared to a simple dispatcher and it was shown that it consistently had a higher probability of successfully reaching a goal state in uncertain environments, performed fewer replans and also executed fewer actions. Hence, Olisipo offers a substantial improvement in performance for disturbed environments.
Cite as

Tomás Ribeiro, Oscar Lima, Michael Cashmore, Andrea Micheli, and Rodrigo Ventura. Olisipo: A Probabilistic Approach to the Adaptable Execution of Deterministic Temporal Plans. In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 15:1-15:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ribeiro_et_al:LIPIcs.TIME.2021.15,
  author =	{Ribeiro, Tom\'{a}s and Lima, Oscar and Cashmore, Michael and Micheli, Andrea and Ventura, Rodrigo},
  title =	{{Olisipo: A Probabilistic Approach to the Adaptable Execution of Deterministic Temporal Plans}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{15:1--15:15},
  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.2021.15},
  URN =		{urn:nbn:de:0030-drops-147913},
  doi =		{10.4230/LIPIcs.TIME.2021.15},
  annote =	{Keywords: Temporal Planning, Temporal Plan Execution, Robotics}
}
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