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International Conference on Principles and Practice of Multi-Agent Systems

PRIMA 2019: PRIMA 2019: Principles and Practice of Multi-Agent Systems pp 354–369Cite as

From Good Intentions to Behaviour Change

Probabilistic Feature Diagrams for Behaviour Support Agents

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11873)

Abstract

Behaviour support technology assists people in organising their daily activities and changing their behaviour. A fundamental notion underlying such supportive technology is that of compliance with behavioural norms: do people indeed perform the desired behaviour? Existing technology employs a rigid implementation of compliance: a norm is either satisfied or not. In practice however, behaviour change norms are less strict: E.g., is a new norm to do sports at least three times a week complied with if it is occasionally only done twice a week? To address this, in this paper we formally specify probabilistic norms through a variant of feature diagrams, enabling a hierarchical decomposition of the desired behaviour and its execution frequencies. Further, we define a new notion of probabilistic norm compliance using a formal hypothesis testing framework. We show that probabilistic norm compliance can be used in a real-world setting by implementing and evaluating our semantics with respect to an existing daily behaviour dataset.

This work is partially financed by the Netherlands Organisation for Scientific Research (NWO) under the research programmes CoreSAEP (639.022.416), SEQUOIA (15474) and StepUp (628.010.006), as well as by the EU under the project 102112 SUCCESS.

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Notes

  1. 1.

    Note that we need to use the infimum here instead of the minimum, since the interval might be left-open.

  2. 2.

    At least when this frequency is a point. However also in case of an interval we need to ask whether it is justified to conclude (non-)compliance if the observed behaviour frequency is close to the edges of the interval.

  3. 3.

    Note that we will have \(l< 0 < u\), so the intervals are indeed sound.

  4. 4.

    The code is available from GitHub repository [20].

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Authors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    Malte S. Kließ & M. Birna van Riemsdijk

  2. University of Twente, Enschede, The Netherlands

    Marielle Stoelinga & M. Birna van Riemsdijk

Authors
  1. Malte S. Kließ
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  2. Marielle Stoelinga
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  3. M. Birna van Riemsdijk
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Correspondence to M. Birna van Riemsdijk .

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Editors and Affiliations

  1. Università degli Studi di Torino, Turin, Italy

    Matteo Baldoni

  2. Utrecht University, Utrecht, The Netherlands

    Mehdi Dastani

  3. Zhejiang University, Hangzhou, China

    Beishui Liao

  4. National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

    Yuko Sakurai

  5. University of Texas at Dallas, Richardson, TX, USA

    Rym Zalila Wenkstern

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Kließ, M.S., Stoelinga, M., van Riemsdijk, M.B. (2019). From Good Intentions to Behaviour Change. In: Baldoni, M., Dastani, M., Liao, B., Sakurai, Y., Zalila Wenkstern, R. (eds) PRIMA 2019: Principles and Practice of Multi-Agent Systems. PRIMA 2019. Lecture Notes in Computer Science(), vol 11873. Springer, Cham. https://doi.org/10.1007/978-3-030-33792-6_22

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  • DOI: https://doi.org/10.1007/978-3-030-33792-6_22

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