5 Search Results for "Gao, Jane"

Document
DOI: 10.4230/LIPIcs.TIME.2024.8
A More Efficient and Informed Algorithm to Check Weak Controllability of Simple Temporal Networks with Uncertainty

Authors: Ajdin Sumic and Thierry Vidal

Published in: LIPIcs, Volume 318, 31st International Symposium on Temporal Representation and Reasoning (TIME 2024)

Abstract
Simple Temporal Networks with Uncertainty (STNU) are a well-known constraint-based model expressing sets of activities (e.g., a schedule or a plan) related by temporal constraints, each having possible durations in the form of convex intervals. Uncertainty comes from some of these durations being contingent, i.e., the agent executing the plan cannot decide the actual duration at execution time. To check that execution will satisfy all the constraints, three levels of controllability exist: the Strong and Dynamic Controllability (SC/DC) has proven both useful in practice and provable in polynomial time, while Weak Controllability (WC) is co-NP-complete and has been left aside. Moreover, controllability checking algorithms are propagation strategies, which have the usual drawback, in case of failure, to prove unable to locate the contingents that explain the source of non-controllability. This paper has three contributions: (1) it substantiates the usefulness of WC in multi-agent systems (MAS) where another agent controls a contingent, and agents agree just before execution on the durations; (2) it provides a new WC-checking algorithm whose performance in practice depends on the network structure and is faster in loosely connected ones; (3) it provides the failing cycles in the network that explain non-WC.
Cite as

Ajdin Sumic and Thierry Vidal. A More Efficient and Informed Algorithm to Check Weak Controllability of Simple Temporal Networks with Uncertainty. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 8:1-8:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{sumic_et_al:LIPIcs.TIME.2024.8,
  author =	{Sumic, Ajdin and Vidal, Thierry},
  title =	{{A More Efficient and Informed Algorithm to Check Weak Controllability of Simple Temporal Networks with Uncertainty}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{8:1--8:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-349-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{318},
  editor =	{Sala, Pietro and Sioutis, Michael and Wang, Fusheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2024.8},
  URN =		{urn:nbn:de:0030-drops-212151},
  doi =		{10.4230/LIPIcs.TIME.2024.8},
  annote =	{Keywords: Temporal constraints satisfaction, uncertainty, STNU, Controllability checking, Explainable inconsistency, Multi-agent planning}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.21
Learning Gradual Typing Performance

Authors: Mohammad Wahiduzzaman Khan, Sheng Chen, and Yi He

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Gradual typing has emerged as a promising typing discipline for reconciling static and dynamic typing, which have respective strengths and shortcomings. Thanks to its promises, gradual typing has gained tremendous momentum in both industry and academia. A main challenge in gradual typing is that, however, the performance of its programs can often be unpredictable, and adding or removing the type of a a single parameter may lead to wild performance swings. Many approaches have been proposed to optimize gradual typing performance, but little work has been done to aid the understanding of the performance landscape of gradual typing and navigating the migration process (which adds type annotations to make programs more static) to avert performance slowdowns. Motivated by this situation, this work develops a machine-learning-based approach to predict the performance of each possible way of adding type annotations to a program. On top of that, many supports for program migrations could be developed, such as finding the most performant neighbor of any given configuration. Our approach gauges runtime overheads of dynamic type checks inserted by gradual typing and uses that information to train a machine learning model, which is used to predict the running time of gradual programs. We have evaluated our approach on 12 Python benchmarks for both guarded and transient semantics. For guarded semantics, our evaluation results indicate that with only 40 training instances generated from each benchmark, the predicted times for all other instances differ on average by 4% from the measured times. For transient semantics, the time difference ratio is higher but the time difference is often within 0.1 seconds.
Cite as

Mohammad Wahiduzzaman Khan, Sheng Chen, and Yi He. Learning Gradual Typing Performance. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 21:1-21:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{khan_et_al:LIPIcs.ECOOP.2024.21,
  author =	{Khan, Mohammad Wahiduzzaman and Chen, Sheng and He, Yi},
  title =	{{Learning Gradual Typing Performance}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{21:1--21:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.21},
  URN =		{urn:nbn:de:0030-drops-208706},
  doi =		{10.4230/LIPIcs.ECOOP.2024.21},
  annote =	{Keywords: Gradual typing performance, type migration, performance prediction, machine learning}
}
Document
DOI: 10.4230/LIPIcs.CP.2024.20
Constraint Modelling with LLMs Using In-Context Learning

Authors: Kostis Michailidis, Dimos Tsouros, and Tias Guns

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

Abstract
Constraint Programming (CP) allows for the modelling and solving of a wide range of combinatorial problems. However, modelling such problems using constraints over decision variables still requires significant expertise, both in conceptual thinking and syntactic use of modelling languages. In this work, we explore the potential of using pre-trained Large Language Models (LLMs) as coding assistants, to transform textual problem descriptions into concrete and executable CP specifications. We present different transformation pipelines with explicit intermediate representations, and we investigate the potential benefit of various retrieval-augmented example selection strategies for in-context learning. We evaluate our approach on 2 datasets from the literature, namely NL4Opt (optimisation) and Logic Grid Puzzles (satisfaction), and a heterogeneous set of exercises from a CP course. The results show that pre-trained LLMs have promising potential for initialising the modelling process, with retrieval-augmented in-context learning significantly enhancing their modelling capabilities.
Cite as

Kostis Michailidis, Dimos Tsouros, and Tias Guns. Constraint Modelling with LLMs Using In-Context Learning. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 20:1-20:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{michailidis_et_al:LIPIcs.CP.2024.20,
  author =	{Michailidis, Kostis and Tsouros, Dimos and Guns, Tias},
  title =	{{Constraint Modelling with LLMs Using In-Context Learning}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{20:1--20:27},
  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.2024.20},
  URN =		{urn:nbn:de:0030-drops-207053},
  doi =		{10.4230/LIPIcs.CP.2024.20},
  annote =	{Keywords: Constraint Modelling, Constraint Acquisition, Constraint Programming, Large Language Models, In-Context Learning, Natural Language Processing, Named Entity Recognition, Retrieval-Augmented Generation, Optimisation}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2024.3
Reachability-Based Response-Time Analysis of Preemptive Tasks Under Global Scheduling

Authors: Pourya Gohari, Jeroen Voeten, and Mitra Nasri

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)

Abstract
Global scheduling reduces the average response times as it can use the available computing cores more efficiently for scheduling ready tasks. However, this flexibility poses challenges in accurately quantifying interference scenarios, often resulting in either conservative response-time analyses or scalability issues. In this paper, we present a new response-time analysis for preemptive periodic tasks (or job sets) subject to release jitter under global job-level fixed-priority (JLFP) scheduling. Our analysis relies on the notion of schedule-abstraction graph (SAG), a reachability-based response-time analysis known for its potential accuracy and efficiency. Up to this point, SAG was limited to non-preemptive tasks due to the complexity of handling preemption when the number of preemptions and the moments they occur are not known beforehand. In this paper, we introduce the concept of time partitions and demonstrate how it facilitates the extension of SAG for preemptive tasks. Moreover, our paper provides the first response-time analysis for the global EDF(k) policy - a JLFP scheduling policy introduced in 2003 to address the Dhall’s effect. Our experiments show that our analysis is significantly more accurate compared to the state-of-the-art analyses. For example, we identify 12 times more schedulable task sets than existing tests for the global EDF policy (e.g., for systems with 6 to 16 tasks, 70% utilization, and 4 cores) with an average runtime of 30 minutes. We show that EDF(k) outperforms global RM and EDF by scheduling on average 24.9% more task sets (e.g., for systems with 2 to 10 cores and 70% utilization). Moreover, for the first time, we show that global JLFP scheduling policies (particularly, global EDF(k)) are able to schedule task sets that are not schedulable using well-known partitioning heuristics.
Cite as

Pourya Gohari, Jeroen Voeten, and Mitra Nasri. Reachability-Based Response-Time Analysis of Preemptive Tasks Under Global Scheduling. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 3:1-3:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{gohari_et_al:LIPIcs.ECRTS.2024.3,
  author =	{Gohari, Pourya and Voeten, Jeroen and Nasri, Mitra},
  title =	{{Reachability-Based Response-Time Analysis of Preemptive Tasks Under Global Scheduling}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{3:1--3:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.3},
  URN =		{urn:nbn:de:0030-drops-203064},
  doi =		{10.4230/LIPIcs.ECRTS.2024.3},
  annote =	{Keywords: Response-time analysis, global scheduling, preemptive, job-level fixed-priority scheduling policy, multicore, schedule-abstraction graph}
}
Document
RANDOM
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2023.54
The Full Rank Condition for Sparse Random Matrices

Authors: Amin Coja-Oghlan, Jane Gao, Max Hahn-Klimroth, Joon Lee, Noela Müller, and Maurice Rolvien

Published in: LIPIcs, Volume 275, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)

Abstract
We derive a sufficient condition for a sparse random matrix with given numbers of non-zero entries in the rows and columns having full row rank. Inspired by low-density parity check codes, the family of random matrices that we investigate is very general and encompasses both matrices over finite fields and {0,1}-matrices over the rationals. The proof combines statistical physics-inspired coupling techniques with local limit arguments.
Cite as

Amin Coja-Oghlan, Jane Gao, Max Hahn-Klimroth, Joon Lee, Noela Müller, and Maurice Rolvien. The Full Rank Condition for Sparse Random Matrices. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 275, pp. 54:1-54:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{cojaoghlan_et_al:LIPIcs.APPROX/RANDOM.2023.54,
  author =	{Coja-Oghlan, Amin and Gao, Jane and Hahn-Klimroth, Max and Lee, Joon and M\"{u}ller, Noela and Rolvien, Maurice},
  title =	{{The Full Rank Condition for Sparse Random Matrices}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)},
  pages =	{54:1--54:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-296-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{275},
  editor =	{Megow, Nicole and Smith, Adam},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2023.54},
  URN =		{urn:nbn:de:0030-drops-188792},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2023.54},
  annote =	{Keywords: random matrices, rank, finite fields, rationals}
}
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