Research Output

An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics.

  We describe an immune inspired approach to achieve self-expression within an ensemble, i.e. enabling an ensemble of autonomic components to dynamically change their coordination pattern during the runtime execution of a given task. Building on previous work using idiotypic networks, we consider robotic swarms in which each robot has a lymph node containing a set of antibodies describing conditions under which different coordination patterns can be applied. Antibodies are shared between robots that come into communication range facilitating collaboration. Tests in simulation in robotic arenas of varying complexity show that the swarm is able to learn suitable patterns and effectively achieve a foraging task, particularly in arenas of high complexity.

  • Date:

    01 January 2013

  • Publication Status:

    Published

  • Publisher

    MIT Press

  • DOI:

    10.7551/978-0-262-31709-2-ch127

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    006.3 Artificial intelligence

Citation

Capodieci, N., Hart, E. & Cabri, G. (2012). An immune network approach for self-adaptive ensembles of autonomic components: a case study in swarm robotics. In Liò, P., Miglino, O., Nicosia, G., Nolfi, S. & Pavone, M. (Eds.). Advances in Artifical Life, Proceedings of ECAL 2013, 864-871. doi:10.7551/978-0-262-31709-2-ch127

Authors

Keywords

Idiotypic networks; robotic swarms; artificial systems;

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