Sensor Placement for Plan Monitoring Using Genetic Programming

Felipe Meneguzzi; Ramon Fraga Pereira; Nir Oren

doi:10.1007/978-3-030-03098-8_40

Sensor Placement for Plan Monitoring Using Genetic Programming

Felipe Meneguzzi^*, Ramon Fraga Pereira, Nir Oren

^*Corresponding author for this work

Autonomy and Verification

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

Abstract

Monitoring plan execution is useful in various multi-agent applications, from agent cooperation to norm enforcement. Realistic environments often impose constraints on the capabilities of such monitoring, limiting the amount and coverage of available sensors. In this paper, we consider the problem of sensor placement within an environment to determine whether some behaviour has occurred. Our model is based on the semantics of planning, and we provide a simple formalism for describing sensors and behaviours in such a model. Given the computational complexity of the sensor placement problem, we investigate heuristic techniques for performing sensor placement, demonstrating that such techniques perform well even in complex domains.

Original language	English
Title of host publication	PRIMA 2018: Principles and Practice of Multi-Agent Systems
Subtitle of host publication	21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings
Editors	Tim Miller, Yuko Sakurai, Itsuki Noda, Bastin Tony Roy Savarimuthu, Tran Cao Son
Place of Publication	Cham
Publisher	Springer Cham
Pages	544–551
Number of pages	8
ISBN (Electronic)	9783030030988
ISBN (Print)	9783030030971
DOIs	https://doi.org/10.1007/978-3-030-03098-8_40
Publication status	Published - 24 Oct 2018
Event	21st International Conference on Principles and Practice of Multi-Agent Systems - Tokyo, Japan Duration: 29 Oct 2018 → 2 Nov 2018

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	11224
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
ISSN (Print)	2945-9133
ISSN (Electronic)	2945-9141

Name	PRIMA: International Conference on Principles and Practice of Multi-Agent Systems
Publisher	Springer

Conference

Conference	21st International Conference on Principles and Practice of Multi-Agent Systems
Abbreviated title	PRIMA 2018
Country/Territory	Japan
City	Tokyo
Period	29/10/18 → 2/11/18

Keywords

genetic programming
monitor plan execution
sensor placement problem
primitive sense
path formula

Access to Document

10.1007/978-3-030-03098-8_40

Cite this

Meneguzzi, F., Pereira, R. F., & Oren, N. (2018). Sensor Placement for Plan Monitoring Using Genetic Programming. In T. Miller, Y. Sakurai, I. Noda, B. T. R. Savarimuthu, & T. C. Son (Eds.), PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings (pp. 544–551). (Lecture Notes in Computer Science; Vol. 11224), (Lecture Notes in Artificial Intelligence), (PRIMA: International Conference on Principles and Practice of Multi-Agent Systems). Springer Cham. https://doi.org/10.1007/978-3-030-03098-8_40

Meneguzzi, Felipe ; Pereira, Ramon Fraga ; Oren, Nir. / Sensor Placement for Plan Monitoring Using Genetic Programming. PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. editor / Tim Miller ; Yuko Sakurai ; Itsuki Noda ; Bastin Tony Roy Savarimuthu ; Tran Cao Son. Cham : Springer Cham, 2018. pp. 544–551 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). (PRIMA: International Conference on Principles and Practice of Multi-Agent Systems).

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abstract = "Monitoring plan execution is useful in various multi-agent applications, from agent cooperation to norm enforcement. Realistic environments often impose constraints on the capabilities of such monitoring, limiting the amount and coverage of available sensors. In this paper, we consider the problem of sensor placement within an environment to determine whether some behaviour has occurred. Our model is based on the semantics of planning, and we provide a simple formalism for describing sensors and behaviours in such a model. Given the computational complexity of the sensor placement problem, we investigate heuristic techniques for performing sensor placement, demonstrating that such techniques perform well even in complex domains.",

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author = "Felipe Meneguzzi and Pereira, {Ramon Fraga} and Nir Oren",

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Meneguzzi, F, Pereira, RF & Oren, N 2018, Sensor Placement for Plan Monitoring Using Genetic Programming. in T Miller, Y Sakurai, I Noda, BTR Savarimuthu & TC Son (eds), PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. Lecture Notes in Computer Science, vol. 11224, Lecture Notes in Artificial Intelligence, PRIMA: International Conference on Principles and Practice of Multi-Agent Systems, Springer Cham, Cham, pp. 544–551, 21st International Conference on Principles and Practice of Multi-Agent Systems, Tokyo, Japan, 29/10/18. https://doi.org/10.1007/978-3-030-03098-8_40

Sensor Placement for Plan Monitoring Using Genetic Programming. / Meneguzzi, Felipe; Pereira, Ramon Fraga; Oren, Nir.
PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. ed. / Tim Miller; Yuko Sakurai; Itsuki Noda; Bastin Tony Roy Savarimuthu; Tran Cao Son. Cham: Springer Cham, 2018. p. 544–551 (Lecture Notes in Computer Science; Vol. 11224), (Lecture Notes in Artificial Intelligence), (PRIMA: International Conference on Principles and Practice of Multi-Agent Systems).

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

TY - GEN

T1 - Sensor Placement for Plan Monitoring Using Genetic Programming

AU - Meneguzzi, Felipe

AU - Pereira, Ramon Fraga

AU - Oren, Nir

PY - 2018/10/24

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N2 - Monitoring plan execution is useful in various multi-agent applications, from agent cooperation to norm enforcement. Realistic environments often impose constraints on the capabilities of such monitoring, limiting the amount and coverage of available sensors. In this paper, we consider the problem of sensor placement within an environment to determine whether some behaviour has occurred. Our model is based on the semantics of planning, and we provide a simple formalism for describing sensors and behaviours in such a model. Given the computational complexity of the sensor placement problem, we investigate heuristic techniques for performing sensor placement, demonstrating that such techniques perform well even in complex domains.

AB - Monitoring plan execution is useful in various multi-agent applications, from agent cooperation to norm enforcement. Realistic environments often impose constraints on the capabilities of such monitoring, limiting the amount and coverage of available sensors. In this paper, we consider the problem of sensor placement within an environment to determine whether some behaviour has occurred. Our model is based on the semantics of planning, and we provide a simple formalism for describing sensors and behaviours in such a model. Given the computational complexity of the sensor placement problem, we investigate heuristic techniques for performing sensor placement, demonstrating that such techniques perform well even in complex domains.

KW - genetic programming

KW - monitor plan execution

KW - sensor placement problem

KW - primitive sense

KW - path formula

U2 - 10.1007/978-3-030-03098-8_40

DO - 10.1007/978-3-030-03098-8_40

M3 - Conference contribution

SN - 9783030030971

T3 - Lecture Notes in Computer Science

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BT - PRIMA 2018: Principles and Practice of Multi-Agent Systems

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A2 - Sakurai, Yuko

A2 - Noda, Itsuki

A2 - Savarimuthu, Bastin Tony Roy

A2 - Son, Tran Cao

PB - Springer Cham

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T2 - 21st International Conference on Principles and Practice of Multi-Agent Systems

Y2 - 29 October 2018 through 2 November 2018

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Meneguzzi F, Pereira RF, Oren N. Sensor Placement for Plan Monitoring Using Genetic Programming. In Miller T, Sakurai Y, Noda I, Savarimuthu BTR, Son TC, editors, PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. Cham: Springer Cham. 2018. p. 544–551. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). (PRIMA: International Conference on Principles and Practice of Multi-Agent Systems). doi: 10.1007/978-3-030-03098-8_40

Sensor Placement for Plan Monitoring Using Genetic Programming

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Conference

Keywords

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