5 Search Results for "Endriss, Ulle"

Document
DOI: 10.4230/LIPIcs.SAT.2024.11
On the Relative Efficiency of Dynamic and Static Top-Down Compilation to Decision-DNNF

Authors: Alexis de Colnet

Published in: LIPIcs, Volume 305, 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)

Abstract
Top-down compilers of CNF formulas to circuits in decision-DNNF (Decomposable Negation Normal Form) have proved to be useful for model counting. These compilers rely on a common set of techniques including DPLL-style exploration of the set of models, caching of residual formulas, and connected components detection. Differences between compilers lie in the variable selection heuristics and in the additional processing techniques they may use. We investigate, from a theoretical perspective, the ability of top-down compilation algorithms to find small decision-DNNF circuits for two different variable selection strategies. Both strategies are guided by a graph of the CNF formula and are inspired by what is done in practice. The first uses a dynamic graph-partitioning approach while the second works with a static tree decomposition. We show that the dynamic approach performs significantly better than the static approach for some formulas, and that the opposite also holds for other formulas. Our lower bounds are proved despite loose settings where the compilation algorithm is only forced to follow its designed variable selection strategy and where everything else, including the many opportunities for tie-breaking, can be handled non-deterministically.
Cite as

Alexis de Colnet. On the Relative Efficiency of Dynamic and Static Top-Down Compilation to Decision-DNNF. In 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 305, pp. 11:1-11:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{decolnet:LIPIcs.SAT.2024.11,
  author =	{de Colnet, Alexis},
  title =	{{On the Relative Efficiency of Dynamic and Static Top-Down Compilation to Decision-DNNF}},
  booktitle =	{27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)},
  pages =	{11:1--11:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-334-8},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{305},
  editor =	{Chakraborty, Supratik and Jiang, Jie-Hong Roland},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2024.11},
  URN =		{urn:nbn:de:0030-drops-205339},
  doi =		{10.4230/LIPIcs.SAT.2024.11},
  annote =	{Keywords: Knowledge compilation, top-down compilation, decision-DNNF Circuits}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2024.63
A Note on Approximating Weighted Nash Social Welfare with Additive Valuations

Authors: Yuda Feng and Shi Li

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)

Abstract
We give the first O(1)-approximation for the weighted Nash Social Welfare problem with additive valuations. The approximation ratio we obtain is e^{1/e} + ε ≈ 1.445 + ε, which matches the best known approximation ratio for the unweighted case [Barman et al., 2018]. Both our algorithm and analysis are simple. We solve a natural configuration LP for the problem, and obtain the allocation of items to agents using a randomized version of the Shmoys-Tardos rounding algorithm developed for unrelated machine scheduling problems [Shmoys and Tardos, 1993]. In the analysis, we show that the approximation ratio of the algorithm is at most the worst gap between the Nash social welfare of the optimum allocation and that of an EF1 allocation, for an unweighted Nash Social Welfare instance with identical additive valuations. This was shown to be at most e^{1/e} ≈ 1.445 by Barman et al. [Barman et al., 2018], leading to our approximation ratio.
Cite as

Yuda Feng and Shi Li. A Note on Approximating Weighted Nash Social Welfare with Additive Valuations. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 63:1-63:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{feng_et_al:LIPIcs.ICALP.2024.63,
  author =	{Feng, Yuda and Li, Shi},
  title =	{{A Note on Approximating Weighted Nash Social Welfare with Additive Valuations}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{63:1--63:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.63},
  URN =		{urn:nbn:de:0030-drops-202068},
  doi =		{10.4230/LIPIcs.ICALP.2024.63},
  annote =	{Keywords: Nash Social Welfare, Configuration LP, Approximation Algorithms}
}
Document
DOI: 10.4230/DagRep.4.5.27
JA4AI – Judgment Aggregation for Artificial Intelligence (Dagstuhl Seminar 14202)

Authors: Franz Dietrich, Ulle Endriss, Davide Grossi, Gabriella Pigozzi, and Marija Slavkovik

Published in: Dagstuhl Reports, Volume 4, Issue 5 (2014)

Abstract
This report documents the programme and the outcomes of Dagstuhl Seminar 14202 on "Judgment Aggregation for Artificial Intelligence". Judgment aggregation is a new group decision-making theory that lies in the intersection of logic and social choice; it studies how to reach group decisions on several logically interconnected issues by aggregation of individual judgments. Until recently research in judgment aggregation was dominated by its originating context of philosophy, political science and law. Presently, however we are witnessing increasing work in judgment aggregation from researchers in computer science. Since researchers from such diverse disciplinary backgrounds working on judgment aggregation each publish within their own discipline with virtually no cross-discipline cooperation on concrete projects, it is essential that they are given an opportunity to connect to each other and become aware of the workings of the other side. This seminar has provided such an opportunity.
Cite as

Franz Dietrich, Ulle Endriss, Davide Grossi, Gabriella Pigozzi, and Marija Slavkovik. JA4AI – Judgment Aggregation for Artificial Intelligence (Dagstuhl Seminar 14202). In Dagstuhl Reports, Volume 4, Issue 5, pp. 27-39, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@Article{dietrich_et_al:DagRep.4.5.27,
  author =	{Dietrich, Franz and Endriss, Ulle and Grossi, Davide and Pigozzi, Gabriella and Slavkovik, Marija},
  title =	{{JA4AI – Judgment Aggregation for Artificial Intelligence (Dagstuhl Seminar 14202)}},
  pages =	{27--39},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{4},
  number =	{5},
  editor =	{Dietrich, Franz and Endriss, Ulle and Grossi, Davide and Pigozzi, Gabriella and Slavkovik, Marija},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.5.27},
  URN =		{urn:nbn:de:0030-drops-46791},
  doi =		{10.4230/DagRep.4.5.27},
  annote =	{Keywords: Judgment Aggregation, Artificial Intelligence, Computational Social Choice, Collective Decision-making}
}
Document
DOI: 10.4230/DagSemProc.07431.1
07431 Abstracts Collection – Computational Issues in Social Choice

Authors: Ulle Endriss, Jérôme Lang, Francesca Rossi, and Tuomas Sandholm

Published in: Dagstuhl Seminar Proceedings, Volume 7431, Computational Issues in Social Choice (2007)

Abstract
From the 21st to the 26th of October 2007, the Dagstuhl Seminar 07431 on ``Computational Issues in Social Choice'' was held at the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their recent research, and ongoing work and open problems were discussed. The abstracts of the talks given during the seminar are collected in this paper. The first section summarises the seminar topics and goals in general. Links to full papers are provided where available.
Cite as

Ulle Endriss, Jérôme Lang, Francesca Rossi, and Tuomas Sandholm. 07431 Abstracts Collection – Computational Issues in Social Choice. In Computational Issues in Social Choice. Dagstuhl Seminar Proceedings, Volume 7431, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{endriss_et_al:DagSemProc.07431.1,
  author =	{Endriss, Ulle and Lang, J\'{e}r\^{o}me and Rossi, Francesca and Sandholm, Tuomas},
  title =	{{07431 Abstracts Collection – Computational Issues in Social Choice}},
  booktitle =	{Computational Issues in Social Choice},
  pages =	{1--19},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7431},
  editor =	{Ulle Endriss and J\'{e}r\^{o}me Lang and Francesca Rossi and Tuomas Sandholm},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07431.1},
  URN =		{urn:nbn:de:0030-drops-12736},
  doi =		{10.4230/DagSemProc.07431.1},
  annote =	{Keywords: Computational social choice, voting theory, fair division, mechanism design, coalition formation, complexity theory, preference representation, algorithms}
}
Document
DOI: 10.4230/DagSemProc.07431.2
07431 Executive Summary – Computational Issues in Social Choice

Authors: Ulle Endriss, Jérôme Lang, Francesca Rossi, and Tuomas Sandholm

Published in: Dagstuhl Seminar Proceedings, Volume 7431, Computational Issues in Social Choice (2007)

Abstract
Computational social choice is an interdisciplinary field of study at the interface of social choice theory and computer science, with knowledge flowing in either direction. On the one hand, computational social choice is concerned with importing concepts and procedures from social choice theory for solving questions that arise in computer science and AI application domains. This is typically the case for managing societies of autonomous agents, which calls for negotiation and voting procedures. On the other hand, computational social choice is concerned with importing notions and methods from computer science for solving questions originally stemming from social choice, for instance by providing new perspectives on the problem of manipulation and control in elections. This Dagstuhl Seminar has been devoted to the presentation of recent results and an exchange of ideas in this growing research field.
Cite as

Ulle Endriss, Jérôme Lang, Francesca Rossi, and Tuomas Sandholm. 07431 Executive Summary – Computational Issues in Social Choice. In Computational Issues in Social Choice. Dagstuhl Seminar Proceedings, Volume 7431, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{endriss_et_al:DagSemProc.07431.2,
  author =	{Endriss, Ulle and Lang, J\'{e}r\^{o}me and Rossi, Francesca and Sandholm, Tuomas},
  title =	{{07431 Executive Summary – Computational Issues in Social Choice}},
  booktitle =	{Computational Issues in Social Choice},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7431},
  editor =	{Ulle Endriss and J\'{e}r\^{o}me Lang and Francesca Rossi and Tuomas Sandholm},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07431.2},
  URN =		{urn:nbn:de:0030-drops-12749},
  doi =		{10.4230/DagSemProc.07431.2},
  annote =	{Keywords: Computational social choice, voting theory, fair division, mechanism design, coalition formation, complexity theory, preference representation, algorithms}
}
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