Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms

Complexity measures and information theory metrics in general have recently been attracting the interest of multi-agent and robotics communities, owing to their capability of capturing relevant features of robot behaviors, while abstracting from implementation details. We believe that theories and t...

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Detalles Bibliográficos
Autores principales: Roli, Andrea, Ligot, Antoine, Birattari, Mauro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Robotics and AI
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805888/
https://www.ncbi.nlm.nih.gov/pubmed/33501145
http://dx.doi.org/10.3389/frobt.2019.00130
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author Roli, Andrea
Ligot, Antoine
Birattari, Mauro
author_facet Roli, Andrea
Ligot, Antoine
Birattari, Mauro
author_sort Roli, Andrea
collection PubMed
description Complexity measures and information theory metrics in general have recently been attracting the interest of multi-agent and robotics communities, owing to their capability of capturing relevant features of robot behaviors, while abstracting from implementation details. We believe that theories and tools from complex systems science and information theory may be fruitfully applied in the near future to support the automatic design of robot swarms and the analysis of their dynamics. In this paper we discuss opportunities and open questions in this scenario.
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spelling pubmed-78058882021-01-25 Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms Roli, Andrea Ligot, Antoine Birattari, Mauro Front Robot AI Robotics and AI Complexity measures and information theory metrics in general have recently been attracting the interest of multi-agent and robotics communities, owing to their capability of capturing relevant features of robot behaviors, while abstracting from implementation details. We believe that theories and tools from complex systems science and information theory may be fruitfully applied in the near future to support the automatic design of robot swarms and the analysis of their dynamics. In this paper we discuss opportunities and open questions in this scenario. Frontiers Media S.A. 2019-11-26 /pmc/articles/PMC7805888/ /pubmed/33501145 http://dx.doi.org/10.3389/frobt.2019.00130 Text en Copyright © 2019 Roli, Ligot and Birattari. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Roli, Andrea
Ligot, Antoine
Birattari, Mauro
Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
title Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
title_full Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
title_fullStr Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
title_full_unstemmed Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
title_short Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
title_sort complexity measures: open questions and novel opportunities in the automatic design and analysis of robot swarms
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805888/
https://www.ncbi.nlm.nih.gov/pubmed/33501145
http://dx.doi.org/10.3389/frobt.2019.00130
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