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International Workshop on Engineering Multi-Agent Systems

EMAS 2017: Engineering Multi-Agent Systems pp 38–55Cite as

Augmented Agents: Contextual Perception and Planning for BDI Architectures

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10738))

Abstract

Context-aware systems are capable of perceiving the physical environment where they are deployed and adapt their behavior, depending on the available information and how it is processed. Ambient Intelligence (AmI) represents context-aware environments that react and respond to the requirements of people. While different models can be used to implement adaptive context-aware systems, BDI multiagent systems are especially suitable for that, due to their belief-based reasoning. Different BDI architectures, however, use different reasoning processes, therefore providing different adaptability levels. In each architecture, contextual information is adherent to a specific belief structure, and the context-related capabilities may vary. We propose a framework that can be used by BDI agents in a multi-architecture scenario in order to modularly acquire context-aware capabilities, such as learning, additional reasoning abilities, and interoperability. When this framework is combined with an existing BDI agent, the result is an augmented agent.

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Notes

  1. 1.

    http://www.fipa.org/specs/fipa00001/.

  2. 2.

    http://www.antlr.org.

  3. 3.

    https://www.martinfowler.com/eaaCatalog/activeRecord.html.

  4. 4.

    https://sourceforge.net/projects/tuprolog/.

  5. 5.

    http://www.mapdb.org.

  6. 6.

    https://github.com/AReallyGoodName/OfflineReverseGeocode.

  7. 7.

    http://jason.sourceforge.net/.

  8. 8.

    http://www.inf.ufrgs.br/prosoft/bdi4jade/.

  9. 9.

    http://gitlab.com/casals/AAF/.

  10. 10.

    https://software.intel.com/en-us/context-sensing-sdk.

  11. 11.

    http://cartago.sourceforge.net/.

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Author information

Authors and Affiliations

  1. Escola Politécnica - Universidade de São Paulo, Av. Prof. Luciano Gualberto, 158 - trav. 3, São Paulo, SP, 05508-900, Brazil

    Arthur Casals & Anarosa A. F. Brandão

  2. Sorbonne Universités, UPMC Université Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu, 75005, Paris, France

    Amal El Fallah-Seghrouchni

Authors
  1. Arthur Casals
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  2. Amal El Fallah-Seghrouchni
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  3. Anarosa A. F. Brandão
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Corresponding authors

Correspondence to Arthur Casals , Amal El Fallah-Seghrouchni or Anarosa A. F. Brandão .

Editor information

Editors and Affiliations

  1. LIP6, Pierre and Marie Curie University, Paris, France

    Amal El Fallah-Seghrouchni

  2. DISI, University of Bologna, Cesena, Forli, Italy

    Alessandro Ricci

  3. Department of Computer Science, New Mexico State University, Las Cruces, New Mexico, USA

    Tran Cao Son

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Casals, A., El Fallah-Seghrouchni, A., Brandão, A.A.F. (2018). Augmented Agents: Contextual Perception and Planning for BDI Architectures. In: El Fallah-Seghrouchni, A., Ricci, A., Son, T. (eds) Engineering Multi-Agent Systems. EMAS 2017. Lecture Notes in Computer Science(), vol 10738. Springer, Cham. https://doi.org/10.1007/978-3-319-91899-0_3

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  • DOI: https://doi.org/10.1007/978-3-319-91899-0_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91898-3

  • Online ISBN: 978-3-319-91899-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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