Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition

Chrysi Filippaki; Grigoris Antoniou; Ioannis Tsamardinos

doi:10.1007/978-3-642-25167-2_6

Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition

Chrysi Filippaki, Grigoris Antoniou, Ioannis Tsamardinos

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

13 Citations (Scopus)

Abstract

In Ambient Assisted Living and other environments the problem is to recognize all of user activities. Due to noisy or incomplete information a naïve recognition system may report activities that are logically inconsistent with each other, e.g., the user is sleeping on the couch and at the same time is watching TV. In this work, we develop a rule-based recognition system for hierarchically-organized activities that returns only logically consistent scenarios. This is achieved by explicitly formulating conflicts as Weighted Partial MaxSAT clauses to be satisfied. The system also has the ability to adjust the desired level of detail of the scenarios returned. This is accomplished by assigning preferences to clauses of the SAT problem. The system is implemented and evaluated in a real Ambient Intelligence experimental space. It is shown to be robust to the presence of noise; the level of detail can easily be adjusted by the use of two preference parameters.

Original language	English
Title of host publication	Ambient Intelligence
Subtitle of host publication	Second International Joint Conference, AmI 2011, Proceedings
Editors	David V. Keyson, Mary Lou Maher, Norbert Streitz, Adrian Cheok, Juan Carlos Augusto, Reiner Wichert, Gwenn Englebienne, Hamid Aghajan, Ben J. A. Kröse
Place of Publication	Berlin
Publisher	Springer-Verlag Berlin Heidelberg
Pages	51-60
Number of pages	10
Volume	7040 LNCS
ISBN (Electronic)	9783642251672
ISBN (Print)	9783642251665
DOIs	https://doi.org/10.1007/978-3-642-25167-2_6
Publication status	Published - 7 Nov 2011
Externally published	Yes
Event	2nd International Joint Conference on Ambient Intelligence - Amsterdam, Netherlands Duration: 16 Nov 2011 → 18 Nov 2011 Conference number: 2

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer-Verlag Berlin Heidelberg
Volume	7040 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Joint Conference on Ambient Intelligence
Abbreviated title	AmI 2011
Country/Territory	Netherlands
City	Amsterdam
Period	16/11/11 → 18/11/11

Access to Document

10.1007/978-3-642-25167-2_6Licence: Unspecified

Cite this

Filippaki, C., Antoniou, G., & Tsamardinos, I. (2011). Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. In D. V. Keyson, M. L. Maher, N. Streitz, A. Cheok, J. C. Augusto, R. Wichert, G. Englebienne, H. Aghajan, & B. J. A. Kröse (Eds.), Ambient Intelligence: Second International Joint Conference, AmI 2011, Proceedings (Vol. 7040 LNCS, pp. 51-60). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7040 LNCS). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-25167-2_6

Filippaki, Chrysi ; Antoniou, Grigoris ; Tsamardinos, Ioannis. / Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. Ambient Intelligence: Second International Joint Conference, AmI 2011, Proceedings. editor / David V. Keyson ; Mary Lou Maher ; Norbert Streitz ; Adrian Cheok ; Juan Carlos Augusto ; Reiner Wichert ; Gwenn Englebienne ; Hamid Aghajan ; Ben J. A. Kröse. Vol. 7040 LNCS Berlin : Springer-Verlag Berlin Heidelberg, 2011. pp. 51-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition",

abstract = "In Ambient Assisted Living and other environments the problem is to recognize all of user activities. Due to noisy or incomplete information a na{\"i}ve recognition system may report activities that are logically inconsistent with each other, e.g., the user is sleeping on the couch and at the same time is watching TV. In this work, we develop a rule-based recognition system for hierarchically-organized activities that returns only logically consistent scenarios. This is achieved by explicitly formulating conflicts as Weighted Partial MaxSAT clauses to be satisfied. The system also has the ability to adjust the desired level of detail of the scenarios returned. This is accomplished by assigning preferences to clauses of the SAT problem. The system is implemented and evaluated in a real Ambient Intelligence experimental space. It is shown to be robust to the presence of noise; the level of detail can easily be adjusted by the use of two preference parameters.",

keywords = "Activity recognition, Conflict Resolution, Rule-based",

author = "Chrysi Filippaki and Grigoris Antoniou and Ioannis Tsamardinos",

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editor = "Keyson, {David V.} and Maher, {Mary Lou} and Norbert Streitz and Adrian Cheok and Augusto, {Juan Carlos} and Reiner Wichert and Gwenn Englebienne and Hamid Aghajan and Kr{\"o}se, {Ben J. A.}",

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Filippaki, C, Antoniou, G & Tsamardinos, I 2011, Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. in DV Keyson, ML Maher, N Streitz, A Cheok, JC Augusto, R Wichert, G Englebienne, H Aghajan & BJA Kröse (eds), Ambient Intelligence: Second International Joint Conference, AmI 2011, Proceedings. vol. 7040 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7040 LNCS, Springer-Verlag Berlin Heidelberg, Berlin, pp. 51-60, 2nd International Joint Conference on Ambient Intelligence, Amsterdam, Netherlands, 16/11/11. https://doi.org/10.1007/978-3-642-25167-2_6

Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. / Filippaki, Chrysi; Antoniou, Grigoris; Tsamardinos, Ioannis.

Ambient Intelligence: Second International Joint Conference, AmI 2011, Proceedings. ed. / David V. Keyson; Mary Lou Maher; Norbert Streitz; Adrian Cheok; Juan Carlos Augusto; Reiner Wichert; Gwenn Englebienne; Hamid Aghajan; Ben J. A. Kröse. Vol. 7040 LNCS Berlin : Springer-Verlag Berlin Heidelberg, 2011. p. 51-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7040 LNCS).

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

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T1 - Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition

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AU - Antoniou, Grigoris

AU - Tsamardinos, Ioannis

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AB - In Ambient Assisted Living and other environments the problem is to recognize all of user activities. Due to noisy or incomplete information a naïve recognition system may report activities that are logically inconsistent with each other, e.g., the user is sleeping on the couch and at the same time is watching TV. In this work, we develop a rule-based recognition system for hierarchically-organized activities that returns only logically consistent scenarios. This is achieved by explicitly formulating conflicts as Weighted Partial MaxSAT clauses to be satisfied. The system also has the ability to adjust the desired level of detail of the scenarios returned. This is accomplished by assigning preferences to clauses of the SAT problem. The system is implemented and evaluated in a real Ambient Intelligence experimental space. It is shown to be robust to the presence of noise; the level of detail can easily be adjusted by the use of two preference parameters.

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PB - Springer-Verlag Berlin Heidelberg

CY - Berlin

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Filippaki C, Antoniou G, Tsamardinos I. Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. In Keyson DV, Maher ML, Streitz N, Cheok A, Augusto JC, Wichert R, Englebienne G, Aghajan H, Kröse BJA, editors, Ambient Intelligence: Second International Joint Conference, AmI 2011, Proceedings. Vol. 7040 LNCS. Berlin: Springer-Verlag Berlin Heidelberg. 2011. p. 51-60. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-25167-2_6

Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition

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