Accounting for observeras partial observability in stochastic goal recognition design

Christabel Wayllace; Sarah Keren; Avigdor Gal; Erez Karpas; William Yeoh; Shlomo Zilberstein

doi:10.3233/FAIA200370

Accounting for observeras partial observability in stochastic goal recognition design

Christabel Wayllace, Sarah Keren, Avigdor Gal, Erez Karpas, William Yeoh, Shlomo Zilberstein

Data and Decision Sciences

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

Abstract

Motivated by security applications, where agent intentions are unknown, actions may have stochastic outcomes, and an observer may have an obfuscated view due to low sensor resolution, we introduce partially-observable states and unobservable actions into a stochastic goal recognition design framework. The proposed model is accompanied by a method for calculating the expected maximal number of steps before the goal of an agent is revealed and a new sensor refinement modification that can be applied to enhance goal recognition. A preliminary empirical evaluation on a range of benchmark applications shows the effectiveness of our approach.

Original language	English
Title of host publication	ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings
Editors	Giuseppe De Giacomo, Alejandro Catala, Bistra Dilkina, Michela Milano, Senen Barro, Alberto Bugarin, Jerome Lang
Pages	2394-2401
Number of pages	8
ISBN (Electronic)	9781643681009
DOIs	https://doi.org/10.3233/FAIA200370
State	Published - 24 Aug 2020
Event	24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Santiago de Compostela, Online, Spain Duration: 29 Aug 2020 → 8 Sep 2020

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	325
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020
Country/Territory	Spain
City	Santiago de Compostela, Online
Period	29/08/20 → 8/09/20

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.3233/FAIA200370

Cite this

Wayllace, C., Keren, S., Gal, A., Karpas, E., Yeoh, W., & Zilberstein, S. (2020). Accounting for observeras partial observability in stochastic goal recognition design. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarin, & J. Lang (Eds.), ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings (pp. 2394-2401). (Frontiers in Artificial Intelligence and Applications; Vol. 325). https://doi.org/10.3233/FAIA200370

Wayllace, Christabel ; Keren, Sarah ; Gal, Avigdor et al. / Accounting for observeras partial observability in stochastic goal recognition design. ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings. editor / Giuseppe De Giacomo ; Alejandro Catala ; Bistra Dilkina ; Michela Milano ; Senen Barro ; Alberto Bugarin ; Jerome Lang. 2020. pp. 2394-2401 (Frontiers in Artificial Intelligence and Applications).

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title = "Accounting for observeras partial observability in stochastic goal recognition design",

abstract = "Motivated by security applications, where agent intentions are unknown, actions may have stochastic outcomes, and an observer may have an obfuscated view due to low sensor resolution, we introduce partially-observable states and unobservable actions into a stochastic goal recognition design framework. The proposed model is accompanied by a method for calculating the expected maximal number of steps before the goal of an agent is revealed and a new sensor refinement modification that can be applied to enhance goal recognition. A preliminary empirical evaluation on a range of benchmark applications shows the effectiveness of our approach.",

author = "Christabel Wayllace and Sarah Keren and Avigdor Gal and Erez Karpas and William Yeoh and Shlomo Zilberstein",

note = "Publisher Copyright: {\textcopyright} 2020 The authors and IOS Press.; 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 ; Conference date: 29-08-2020 Through 08-09-2020",

year = "2020",

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doi = "10.3233/FAIA200370",

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series = "Frontiers in Artificial Intelligence and Applications",

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editor = "{De Giacomo}, Giuseppe and Alejandro Catala and Bistra Dilkina and Michela Milano and Senen Barro and Alberto Bugarin and Jerome Lang",

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Wayllace, C, Keren, S , Gal, A , Karpas, E, Yeoh, W & Zilberstein, S 2020, Accounting for observeras partial observability in stochastic goal recognition design. in G De Giacomo, A Catala, B Dilkina, M Milano, S Barro, A Bugarin & J Lang (eds), ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings. Frontiers in Artificial Intelligence and Applications, vol. 325, pp. 2394-2401, 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020, Santiago de Compostela, Online, Spain, 29/08/20. https://doi.org/10.3233/FAIA200370

Accounting for observeras partial observability in stochastic goal recognition design. / Wayllace, Christabel; Keren, Sarah ; Gal, Avigdor et al.
ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings. ed. / Giuseppe De Giacomo; Alejandro Catala; Bistra Dilkina; Michela Milano; Senen Barro; Alberto Bugarin; Jerome Lang. 2020. p. 2394-2401 (Frontiers in Artificial Intelligence and Applications; Vol. 325).

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

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Wayllace C, Keren S , Gal A , Karpas E, Yeoh W, Zilberstein S. Accounting for observeras partial observability in stochastic goal recognition design. In De Giacomo G, Catala A, Dilkina B, Milano M, Barro S, Bugarin A, Lang J, editors, ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings. 2020. p. 2394-2401. (Frontiers in Artificial Intelligence and Applications). doi: 10.3233/FAIA200370

Accounting for observeras partial observability in stochastic goal recognition design

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