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Norm Refinement and Design through Inductive Learning

  • Conference paper
Coordination, Organizations, Institutions, and Norms in Agent Systems VI (COIN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6541))

Abstract

In the physical world, the rules governing behaviour are debugged by observing an outcome that was not intended and the addition of new constraints to prevent the attainment of that outcome. We propose a similar approach to support the incremental development of normative frameworks (also called institutions) and demonstrate how this works through the validation and synthesis of normative rules using model generation and inductive learning. This is achieved by the designer providing a set of use cases, comprising collections of event traces that describe how the system is used along with the desired outcome with respect to the normative framework. The model generator encodes the description of the current behaviour of the system. The current specification and the traces for which current behaviour and expected behaviour do not match are given to the learning framework to propose new rules that revise the existing norm set in order to inhibit the unwanted behaviour. The elaboration of a normative system can then be viewed as a semi-automatic, iterative process for the detection of incompleteness or incorrectness of the existing normative rules, with respect to desired properties, and the construction of potential additional rules for the normative system.

This work is partially supported through the EU Framework 7 project ALIVE (FP7-IST-215890), and the EPSRC PRiMMA project (EP/F023294/1).

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Author information

Authors and Affiliations

  1. Department of Computing, Imperial College London, UK

    Domenico Corapi & Alessandra Russo

  2. Department of Computer Science, University of Bath, UK

    Marina De Vos & Julian Padget

  3. National Institute of Informatics, Japan

    Ken Satoh

Authors
  1. Domenico Corapi
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  2. Marina De Vos
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  3. Julian Padget
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  4. Alessandra Russo
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  5. Ken Satoh
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Bath, BA2 7AY, Bath, UK

    Marina De Vos

  2. Università della Svizzera italiana, via G. Buffi 13, 6900, Lugano, Switzerland

    Nicoletta Fornara

  3. Department of Electrical & Electronic Engineering, Imperial College London, SW7 2BT, UK

    Jeremy V. Pitt

  4. Department of Information and Communication Systems Engineering, University of the Aegean, 83200, Karlovassi, Samos, Greece

    George Vouros

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Corapi, D., De Vos, M., Padget, J., Russo, A., Satoh, K. (2011). Norm Refinement and Design through Inductive Learning. In: De Vos, M., Fornara, N., Pitt, J.V., Vouros, G. (eds) Coordination, Organizations, Institutions, and Norms in Agent Systems VI. COIN 2010. Lecture Notes in Computer Science(), vol 6541. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21268-0_5

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  • DOI: https://doi.org/10.1007/978-3-642-21268-0_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21267-3

  • Online ISBN: 978-3-642-21268-0

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