Sensing as a complexity measure

Shaull Almagor; Denis Kuperberg; Orna Kupferman

doi:10.1007/978-3-319-60252-3_1

Sensing as a complexity measure

Shaull Almagor, Denis Kuperberg, Orna Kupferman^*

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The size of deterministic automata required for recognizing regular and ω-regular languages is a well-studied measure for the complexity of languages. We introduce and study a new complexity measure, based on the sensing required for recognizing the language. Intuitively, the sensing cost quantifies the detail in which a random input word has to be read in order to decide its membership in the language. We study the sensing cost of regular and ω-regular languages, as well as applications of the study in practice, especially in the monitoring and synthesis of reactive systems.

Original language	American English
Title of host publication	Descriptional Complexity of Formal Systems - 19th IFIP WG 1.02 International Conference, DCFS 2017, Proceedings
Editors	Giovanni Pighizzini, Cezar Campeanu
Publisher	Springer Verlag
Pages	3-15
Number of pages	13
ISBN (Print)	9783319602516
DOIs	https://doi.org/10.1007/978-3-319-60252-3_1
State	Published - 2017
Event	19th International Conference of Descriptional Complexity of Formal Systems, DCFS 2017 - Milano, Italy Duration: 3 Jul 2017 → 5 Jul 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10316 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference of Descriptional Complexity of Formal Systems, DCFS 2017
Country/Territory	Italy
City	Milano
Period	3/07/17 → 5/07/17

Bibliographical note

Funding Information:
The paper gives an overview of the technical results in the papers [, ]. The research leading to these results has received funding from the European Research Council under the European Union’s 7th Framework Programme (FP7/2007-2013, ERC grant no. 278410).

Publisher Copyright:
© IFIP International Federation for Information Processing 2017.

Access to Document

10.1007/978-3-319-60252-3_1

Cite this

Almagor, S., Kuperberg, D., & Kupferman, O. (2017). Sensing as a complexity measure. In G. Pighizzini, & C. Campeanu (Eds.), Descriptional Complexity of Formal Systems - 19th IFIP WG 1.02 International Conference, DCFS 2017, Proceedings (pp. 3-15). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10316 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-60252-3_1

Almagor, Shaull ; Kuperberg, Denis ; Kupferman, Orna. / Sensing as a complexity measure. Descriptional Complexity of Formal Systems - 19th IFIP WG 1.02 International Conference, DCFS 2017, Proceedings. editor / Giovanni Pighizzini ; Cezar Campeanu. Springer Verlag, 2017. pp. 3-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Sensing as a complexity measure",

abstract = "The size of deterministic automata required for recognizing regular and ω-regular languages is a well-studied measure for the complexity of languages. We introduce and study a new complexity measure, based on the sensing required for recognizing the language. Intuitively, the sensing cost quantifies the detail in which a random input word has to be read in order to decide its membership in the language. We study the sensing cost of regular and ω-regular languages, as well as applications of the study in practice, especially in the monitoring and synthesis of reactive systems.",

author = "Shaull Almagor and Denis Kuperberg and Orna Kupferman",

note = "Funding Information: The paper gives an overview of the technical results in the papers [, ]. The research leading to these results has received funding from the European Research Council under the European Union{\textquoteright}s 7th Framework Programme (FP7/2007-2013, ERC grant no. 278410). Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2017.; 19th International Conference of Descriptional Complexity of Formal Systems, DCFS 2017 ; Conference date: 03-07-2017 Through 05-07-2017",

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doi = "10.1007/978-3-319-60252-3_1",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Almagor, S, Kuperberg, D & Kupferman, O 2017, Sensing as a complexity measure. in G Pighizzini & C Campeanu (eds), Descriptional Complexity of Formal Systems - 19th IFIP WG 1.02 International Conference, DCFS 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10316 LNCS, Springer Verlag, pp. 3-15, 19th International Conference of Descriptional Complexity of Formal Systems, DCFS 2017, Milano, Italy, 3/07/17. https://doi.org/10.1007/978-3-319-60252-3_1

Sensing as a complexity measure. / Almagor, Shaull; Kuperberg, Denis; Kupferman, Orna.
Descriptional Complexity of Formal Systems - 19th IFIP WG 1.02 International Conference, DCFS 2017, Proceedings. ed. / Giovanni Pighizzini; Cezar Campeanu. Springer Verlag, 2017. p. 3-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10316 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2017

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N2 - The size of deterministic automata required for recognizing regular and ω-regular languages is a well-studied measure for the complexity of languages. We introduce and study a new complexity measure, based on the sensing required for recognizing the language. Intuitively, the sensing cost quantifies the detail in which a random input word has to be read in order to decide its membership in the language. We study the sensing cost of regular and ω-regular languages, as well as applications of the study in practice, especially in the monitoring and synthesis of reactive systems.

AB - The size of deterministic automata required for recognizing regular and ω-regular languages is a well-studied measure for the complexity of languages. We introduce and study a new complexity measure, based on the sensing required for recognizing the language. Intuitively, the sensing cost quantifies the detail in which a random input word has to be read in order to decide its membership in the language. We study the sensing cost of regular and ω-regular languages, as well as applications of the study in practice, especially in the monitoring and synthesis of reactive systems.

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Almagor S, Kuperberg D, Kupferman O. Sensing as a complexity measure. In Pighizzini G, Campeanu C, editors, Descriptional Complexity of Formal Systems - 19th IFIP WG 1.02 International Conference, DCFS 2017, Proceedings. Springer Verlag. 2017. p. 3-15. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-60252-3_1

Sensing as a complexity measure

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