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On the evolution of autonomous decision-making and communication in collective robotics

In this thesis, we use evolutionary robotics techniques to automatically design and synthesise<p>behaviour for groups of simulated and real robots. Our contribution will be on<p>the design of non-trivial individual and collective behaviour; decisions about solitary or<p>social behaviour will be temporal and they will be interdependent with communicative<p>acts. In particular, we study time-based decision-making in a social context: how the<p>experiences of robots unfold in time and how these experiences influence their interaction<p>with the rest of the group. We propose three experiments based on non-trivial real-world<p>cooperative scenarios. First, we study social cooperative categorisation; signalling and<p>communication evolve in a task where the cooperation among robots is not a priori required.<p>The communication and categorisation skills of the robots are co-evolved from<p>scratch, and the emerging time-dependent individual and social behaviour are successfully<p>tested on real robots. Second, we show on real hardware evidence of the success of evolved<p>neuro-controllers when controlling two autonomous robots that have to grip each other<p>(autonomously self-assemble). Our experiment constitutes the first fully evolved approach<p>on such a task that requires sophisticated and fine sensory-motor coordination, and it<p>highlights the minimal conditions to achieve assembly in autonomous robots by reducing<p>the assumptions a priori made by the experimenter to a functional minimum. Third, we<p>present the first work in the literature to deal with the design of homogeneous control<p>mechanisms for morphologically heterogeneous robots, that is, robots that do not share<p>the same hardware characteristics. We show how artificial evolution designs individual<p>behaviours and communication protocols that allow the cooperation between robots of<p>different types, by using dynamical neural networks that specialise on-line, depending on<p>the nature of the morphology of each robot. The experiments briefly described above<p>contribute to the advancement of the state of the art in evolving neuro-controllers for<p>collective robotics both from an application-oriented, engineering point of view, as well as<p>from a more theoretical point of view. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Identiferoai:union.ndltd.org:ulb.ac.be/oai:dipot.ulb.ac.be:2013/210445
Date10 November 2008
CreatorsAmpatzis, Christos
ContributorsDorigo, Marco, Bersini, Hugues, Izzo, Dario, Decaester, Christine, Noble, Jason, Tuci, Elio, Birattari, Mauro, Robert, Frédéric
PublisherUniversite Libre de Bruxelles, Université libre de Bruxelles, Faculté des sciences appliquées – Informatique, Bruxelles
Source SetsUniversité libre de Bruxelles
LanguageFrench
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/doctoralThesis, info:ulb-repo/semantics/doctoralThesis, info:ulb-repo/semantics/openurl/vlink-dissertation
Format1 v., 2 full-text file(s): application/pdf | application/pdf
Rights2 full-text file(s): info:eu-repo/semantics/restrictedAccess | info:eu-repo/semantics/openAccess

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