Embodied evolution of self-organised aggregation by cultural propagation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

Colleges, School and Institutes

Abstract

Probabilistic aggregation is a self-organised behaviour studied in swarm robotics. It aims at gathering a population of robots in the same place, in order to favour the execution of other more complex collective behaviours or tasks. However, probabilistic aggregation is extremely sensitive to experimental conditions, and thus requires specific parameter tuning for different conditions such as population size or density. To tackle this challenge, in this paper, we present a novel embodied evolution approach for swarm robotics based on social dynamics. This idea hinges on the cultural evolution metaphor, which postulates that good ideas spread widely in a population. Thus, we propose that good parameter settings can spread following a social dynamics process. Testing this idea on probabilistic aggregation and using the minimal naming game to emulate social dynamics, we observe a significant improvement in the scalability of the aggregation process.

Details

Original languageEnglish
Title of host publicationSwarm Intelligence
Subtitle of host publication11th International Conference, ANTS 2018, Rome, Italy, October 29–31, 2018, Proceedings
EditorsMarco Dorigo, Mauro Birattari, Christian Blum , Anders L. Christensen, Andreagiovanni Reina, Vito Trianni
Publication statusPublished - 2018
Event11th International Conference on Swarm Intelligence (ANTS 2018) - Rome, Italy
Duration: 29 Oct 201831 Oct 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11172
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Swarm Intelligence (ANTS 2018)
Abbreviated titleANTS 2018
CountryItaly
CityRome
Period29/10/1831/10/18

Keywords

  • swarm robotics