Cultural transmission in robotic swarms through RFID cards

Josh Brandoff*, Hiroki Sayama

*Corresponding author for this work

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

1 Citation (Scopus)


The recent development of economical highcapacity RFID cards has opened up a new opportunity for stigmergic robotic swarms. Through these cards, robotic agents can dynamically exchange more complex, logical information, such as the whole set of their behavioral rules or "culture". To the best of our knowledge, this opportunity has not been explored in swarm robotics and other collective robotics communities. We have developed a prototypical robotic swarm system comprised of 8 low-cost OPEN-ROBOTs with the ability to avoid obstacles and exchange information with low-capacity RFID cards randomly distributed in an environment. To evaluate the effectiveness of our RFID-based cultural transmission technique, we created a realistic computer simulation to test the swarm's competence in mapping a virtual multi-room house covered with 80 low-capacity RFID cards in under one hour. By increasing the probability that a robot adopts a random exploration behavior different from one "marked" on a card, the swarm is able to cover more of an environment with higher consistency between trials. This result indicates that encouraging diversity among agents supports robust emergent behavior and lays the groundwork for future experiments with higher-capacity RFID cards.

Original languageEnglish
Title of host publication2009 IEEE Symposium on Artificial Life, ALIFE 2009 - Proceedings
Number of pages8
Publication statusPublished - 2009 Jul 20
Externally publishedYes
Event2009 IEEE Symposium on Artificial Life, ALIFE 2009 - Nashville, TN, United States
Duration: 2009 Mar 302009 Apr 2

Publication series

Name2009 IEEE Symposium on Artificial Life, ALIFE 2009 - Proceedings


Other2009 IEEE Symposium on Artificial Life, ALIFE 2009
Country/TerritoryUnited States
CityNashville, TN

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition


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