5 Search Results for "Payne, Robert D."

Document
DOI: 10.4230/LIPIcs.SoCG.2025.72
Geometric Bipartite Matching Based Exact Algorithms for Server Problems

Authors: Sharath Raghvendra, Pouyan Shirzadian, and Rachita Sowle

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
For any given metric space, obtaining an offline optimal solution to the classical k-server problem can be reduced to solving a minimum-cost partial bipartite matching between two point sets A and B within that metric space. For d-dimensional 𝓁_p metric space, we present an Õ(min{nk, n^{2-1/(2d+1)}log Δ}⋅ Φ(n)) time algorithm for solving this instance of minimum-cost partial bipartite matching; here, Δ represents the spread of the point set, and Φ(n) is the query/update time of a d-dimensional dynamic weighted nearest neighbor data structure. Our algorithm improves upon prior algorithms that require at least Ω(nkΦ(n)) time. The design of minimum-cost (partial) bipartite matching algorithms that make sub-quadratic queries to a weighted nearest-neighbor data structure, even for bounded spread instances, is a major open problem in computational geometry. We resolve this problem at least for the instances that are generated by the offline version of the k-server problem. Our algorithm employs a hierarchical partitioning approach, dividing the points of A∪ B into rectangles. It maintains a partial minimum-cost matching where any point b ∈ B is either matched to another point a ∈ A or to the boundary of the rectangle it is located in. The algorithm involves iteratively merging pairs of rectangles by erasing the shared boundary between them and recomputing the minimum-cost partial matching. This continues until all boundaries are erased and we obtain the desired minimum-cost partial matching of A and B. We exploit geometry in our analysis to show that each point participates in only Õ(n^{1-1/(2d+1)}log Δ) number of augmenting paths, leading to a total execution time of Õ(n^{2-1/(2d+1)}Φ(n)log Δ). We also show that, for the 𝓁₁ norm and d dimensions, any algorithm that can solve instances of the offline n-server problem with an exponential spread in T(n) time can be used to compute minimum-cost bipartite matching in a complete graph defined on two (d-1)-dimensional point sets under the 𝓁₁ norm within T(n) time. This suggests that removing spread from the execution time of our algorithm may be difficult as it immediately results in a sub-quadratic algorithm for bipartite matching under the 𝓁₁ norm.
Cite as

Sharath Raghvendra, Pouyan Shirzadian, and Rachita Sowle. Geometric Bipartite Matching Based Exact Algorithms for Server Problems. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 72:1-72:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{raghvendra_et_al:LIPIcs.SoCG.2025.72,
  author =	{Raghvendra, Sharath and Shirzadian, Pouyan and Sowle, Rachita},
  title =	{{Geometric Bipartite Matching Based Exact Algorithms for Server Problems}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{72:1--72:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.72},
  URN =		{urn:nbn:de:0030-drops-232240},
  doi =		{10.4230/LIPIcs.SoCG.2025.72},
  annote =	{Keywords: Minimum-Cost Bipartite Matching, Server Problems, Primal-Dual Approach}
}
Document
Survey
DOI: 10.4230/TGDK.2.1.1
Towards Representing Processes and Reasoning with Process Descriptions on the Web

Authors: Andreas Harth, Tobias Käfer, Anisa Rula, Jean-Paul Calbimonte, Eduard Kamburjan, and Martin Giese

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
We work towards a vocabulary to represent processes and temporal logic specifications as graph-structured data. Different fields use incompatible terminologies for describing essentially the same process-related concepts. In addition, processes can be represented from different perspectives and levels of abstraction: both state-centric and event-centric perspectives offer distinct insights into the underlying processes. In this work, we strive to unify the representation of processes and related concepts by leveraging the power of knowledge graphs. We survey approaches to representing processes and reasoning with process descriptions from different fields and provide a selection of scenarios to help inform the scope of a unified representation of processes. We focus on processes that can be executed and observed via web interfaces. We propose to provide a representation designed to combine state-centric and event-centric perspectives while incorporating temporal querying and reasoning capabilities on temporal logic specifications. A standardised vocabulary and representation for processes and temporal specifications would contribute towards bridging the gap between the terminologies from different fields and fostering the broader application of methods involving temporal logics, such as formal verification and program synthesis.
Cite as

Andreas Harth, Tobias Käfer, Anisa Rula, Jean-Paul Calbimonte, Eduard Kamburjan, and Martin Giese. Towards Representing Processes and Reasoning with Process Descriptions on the Web. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 1:1-1:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{harth_et_al:TGDK.2.1.1,
  author =	{Harth, Andreas and K\"{a}fer, Tobias and Rula, Anisa and Calbimonte, Jean-Paul and Kamburjan, Eduard and Giese, Martin},
  title =	{{Towards Representing Processes and Reasoning with Process Descriptions on the Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:32},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.1},
  URN =		{urn:nbn:de:0030-drops-198583},
  doi =		{10.4230/TGDK.2.1.1},
  annote =	{Keywords: Process modelling, Process ontology, Temporal logic, Web services}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.13
Autonomy in the Age of Knowledge Graphs: Vision and Challenges

Authors: Jean-Paul Calbimonte, Andrei Ciortea, Timotheus Kampik, Simon Mayer, Terry R. Payne, Valentina Tamma, and Antoine Zimmermann

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
In this position paper, we propose that Knowledge Graphs (KGs) are one of the prime approaches to support the programming of autonomous software systems at the knowledge level. From this viewpoint, we survey how KGs can support different dimensions of autonomy in such systems: For example, the autonomy of systems with respect to their environment, or with respect to organisations; and we discuss related practical and research challenges. We emphasise that KGs need to be able to support systems of autonomous software agents that are themselves highly heterogeneous, which limits how these systems may use KGs. Furthermore, these heterogeneous software agents may populate highly dynamic environments, which implies that they require adaptive KGs. The scale of the envisioned systems - possibly stretching to the size of the Internet - highlights the maintainability of the underlying KGs that need to contain large-scale knowledge, which requires that KGs are maintained jointly by humans and machines. Furthermore, autonomous agents require procedural knowledge, and KGs should hence be explored more towards the provisioning of such knowledge to augment autonomous behaviour. Finally, we highlight the importance of modelling choices, including with respect to the selected abstraction level when modelling and with respect to the provisioning of more expressive constraint languages.
Cite as

Jean-Paul Calbimonte, Andrei Ciortea, Timotheus Kampik, Simon Mayer, Terry R. Payne, Valentina Tamma, and Antoine Zimmermann. Autonomy in the Age of Knowledge Graphs: Vision and Challenges. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 13:1-13:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{calbimonte_et_al:TGDK.1.1.13,
  author =	{Calbimonte, Jean-Paul and Ciortea, Andrei and Kampik, Timotheus and Mayer, Simon and Payne, Terry R. and Tamma, Valentina and Zimmermann, Antoine},
  title =	{{Autonomy in the Age of Knowledge Graphs: Vision and Challenges}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{13:1--13:22},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.13},
  URN =		{urn:nbn:de:0030-drops-194872},
  doi =		{10.4230/TGDK.1.1.13},
  annote =	{Keywords: Knowledge graphs, Autonomous Systems}
}
Document
Position
DOI: 10.4230/TGDK.1.1.5
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities

Authors: Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and graph-structured. The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with the ultimate aim to advance scientific discovery. In this survey and position paper, we discuss recent developments and advances in the use of graph-based technologies in life sciences and set out a vision for how these technologies will impact these fields into the future. We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial intelligence applications to support explanations (explainable AI). We select a few exemplary use cases for each topic, discuss the challenges and open research questions within these topics, and conclude with a perspective and outlook that summarizes the overarching challenges and their potential solutions as a guide for future research.
Cite as

Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma. Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 5:1-5:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{chen_et_al:TGDK.1.1.5,
  author =	{Chen, Jiaoyan and Dong, Hang and Hastings, Janna and Jim\'{e}nez-Ruiz, Ernesto and L\'{o}pez, Vanessa and Monnin, Pierre and Pesquita, Catia and \v{S}koda, Petr and Tamma, Valentina},
  title =	{{Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:33},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.5},
  URN =		{urn:nbn:de:0030-drops-194791},
  doi =		{10.4230/TGDK.1.1.5},
  annote =	{Keywords: Knowledge graphs, Life science, Knowledge discovery, Explainable AI}
}
Document
Invited Paper
DOI: 10.4230/OASIcs.CMN.2014.2
Narrative in the Operations Process (Invited Paper)

Authors: Sohail A. Shaikh and Robert D. Payne

Published in: OASIcs, Volume 41, 2014 Workshop on Computational Models of Narrative

Abstract
To counter the threat posed by adversary information activities, the U.S. Army has developed a new warfighting function, "engagement" which will institutionalize lessons learned over the past decade of warfare. Like mission command, sustainment, intelligence, or other warfighting functions that are critical to the successful prosecution of warfare, the ability to engage a population in a way that is credible, logical and emotional to people is far more likely to compel them to the national will than lethal options. The military as a whole, and more specifically the strategic land forces (consisting of the Army, Marine Corps and U.S. Special Operations Command), are now in the process of determining the best way to implement engagement as a full-fledged function of strategic landpower. This paper will make the case that narrative is one of the key elements of engagement. The past ten years of conflict in Iraq and Afghanistan have taught the U.S. military that future wars of the 21st century will be characterized by low intensity conflicts in increasingly complex environments. In spite of the U.S. military's preponderance of power and overwhelming ability to dominate an adversary in traditional maneuver warfare, resilient insurgencies have demonstrated their potential to successfully conduct asymmetric warfare. This has proven successful, at least in the near term, when employed against U.S. and coalition forces. While the military has consistently fulfilled its responsibility to defeat the enemy's conventional forces and seize, occupy and defend land areas, it has not been as successful in the war of ideologies. We will outline how narrative should align to the military decision making process, and give an example of a successful narrative operation (Voices of Moderate Islam) that can serve as vignette for demonstrating how to conduct a narrative in U.S. led operations. We also make the case for greater academic focus on the topic of narrative in a military context: The acceptance of "engagement" as a function of warfare is still premature so a close cooperation is necessary between the military and academic disciplines that study narrative. Collaborative partnerships with academia will be critical. Finally, we argue that the doctrinal institutionalization of narrative as part of the military decision making process (MDMP) will enable military commanders to effectively achieve the desired goals of national policy.
Cite as

Sohail A. Shaikh and Robert D. Payne. Narrative in the Operations Process (Invited Paper). In 2014 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 41, pp. 2-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{shaikh_et_al:OASIcs.CMN.2014.2,
  author =	{Shaikh, Sohail A. and Payne, Robert D.},
  title =	{{Narrative in the Operations Process}},
  booktitle =	{2014 Workshop on Computational Models of Narrative},
  pages =	{2--8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-71-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{41},
  editor =	{Finlayson, Mark A. and Meister, Jan Christoph and Bruneau, Emile G.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2014.2},
  URN =		{urn:nbn:de:0030-drops-46399},
  doi =		{10.4230/OASIcs.CMN.2014.2},
  annote =	{Keywords: narrative, engagement, military, operations, doctrine}
}
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