Literature DB >> 33501145

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

Andrea Roli1, Antoine Ligot2, Mauro Birattari2.   

Abstract

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.
Copyright © 2019 Roli, Ligot and Birattari.

Entities:  

Keywords:  automatic design; complexity measures; evolutionary robotics; information theory; swarm robotics

Year:  2019        PMID: 33501145      PMCID: PMC7805888          DOI: 10.3389/frobt.2019.00130

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  23 in total

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Journal:  Sci Robot       Date:  2018-01-31

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Authors:  Hui Xie; Mengmeng Sun; Xinjian Fan; Zhihua Lin; Weinan Chen; Lei Wang; Lixin Dong; Qiang He
Journal:  Sci Robot       Date:  2019-03-20

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Authors:  Federico Da Rold
Journal:  Neural Netw       Date:  2018-03-27

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Authors:  David Balduzzi; Giulio Tononi
Journal:  PLoS Comput Biol       Date:  2008-06-13       Impact factor: 4.475

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Authors:  Max Lungarella; Olaf Sporns
Journal:  PLoS Comput Biol       Date:  2006-10-27       Impact factor: 4.475

8.  Information Flow through a Model of the C. elegans Klinotaxis Circuit.

Authors:  Eduardo J Izquierdo; Paul L Williams; Randall D Beer
Journal:  PLoS One       Date:  2015-10-14       Impact factor: 3.240

9.  Ultra-extensible ribbon-like magnetic microswarm.

Authors:  Jiangfan Yu; Ben Wang; Xingzhou Du; Qianqian Wang; Li Zhang
Journal:  Nat Commun       Date:  2018-08-21       Impact factor: 14.919

10.  Keep your options open: an information-based driving principle for sensorimotor systems.

Authors:  Alexander S Klyubin; Daniel Polani; Chrystopher L Nehaniv
Journal:  PLoS One       Date:  2008-12-24       Impact factor: 3.240

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