Inferring Temporal Structure from Predictability in Bumblebee Learning Flight

Meyer S, Bertrand OJN, Egelhaaf M, Hammer B (2018)
In: Intelligent Data Engineering and Automated Learning – IDEAL 2018. Yin H, Camacho D, Novais P, Tallón-Ballesteros AJ (Eds); Lecture Notes in Computer Science, 11314. Cham: Springer International Publishing: 508-519.

Download
Es wurde kein Volltext hochgeladen. Nur Publikationsnachweis!
Sammelwerksbeitrag | Veröffentlicht | Englisch
Autor
; ; ;
Herausgeber
; ; ;
Abstract / Bemerkung
Insects are succeeding in remarkable navigational tasks. Bumblebees, for example, are capable of learning their nest location with sophisticated flight manoeuvres, forming a so-called learning flight. The learning flights - thought to be partially pre-programmed - enable the bumblebee to memorise spatial relations between its inconspicuous nest entrance and environmental cues. To date, environmental features (e.g. object positions on the eyes) and learning experience of the insect were used to describe the flights, but its structure, thought to facilitated learning, has not been investigated systematically. In this work, we present a novel approach, to examine whether and in which time span flight behaviour is predictable based on intrinsic properties only rather than external sensory information. We study the temporal composition of learning flights by estimating the smoothness of the underlying process. We then use echo state networks (ESN) and linear models (ARIMA) to predict the bumblebee trajectory from its past motion and identify different time-scales in learning flights using their prediction-power. We found that direct visual information is not necessary within a 200ms time-window to explain the bumblebee behaviour during its learning flight.
Erscheinungsjahr
Buchtitel
Intelligent Data Engineering and Automated Learning – IDEAL 2018
Band
11314
Seite(n)
508-519
PUB-ID

Zitieren

Meyer S, Bertrand OJN, Egelhaaf M, Hammer B. Inferring Temporal Structure from Predictability in Bumblebee Learning Flight. In: Yin H, Camacho D, Novais P, Tallón-Ballesteros AJ, eds. Intelligent Data Engineering and Automated Learning – IDEAL 2018. Lecture Notes in Computer Science. Vol 11314. Cham: Springer International Publishing; 2018: 508-519.
Meyer, S., Bertrand, O. J. N., Egelhaaf, M., & Hammer, B. (2018). Inferring Temporal Structure from Predictability in Bumblebee Learning Flight. In H. Yin, D. Camacho, P. Novais, & A. J. Tallón-Ballesteros (Eds.), Lecture Notes in Computer Science: Vol. 11314. Intelligent Data Engineering and Automated Learning – IDEAL 2018 (pp. 508-519). Cham: Springer International Publishing. doi:10.1007/978-3-030-03493-1_53
Meyer, S., Bertrand, O. J. N., Egelhaaf, M., and Hammer, B. (2018). “Inferring Temporal Structure from Predictability in Bumblebee Learning Flight” in Intelligent Data Engineering and Automated Learning – IDEAL 2018, Yin, H., Camacho, D., Novais, P., and Tallón-Ballesteros, A. J. eds. Lecture Notes in Computer Science, vol. 11314, (Cham: Springer International Publishing), 508-519.
Meyer, S., et al., 2018. Inferring Temporal Structure from Predictability in Bumblebee Learning Flight. In H. Yin, et al., eds. Intelligent Data Engineering and Automated Learning – IDEAL 2018. Lecture Notes in Computer Science. no.11314 Cham: Springer International Publishing, pp. 508-519.
S. Meyer, et al., “Inferring Temporal Structure from Predictability in Bumblebee Learning Flight”, Intelligent Data Engineering and Automated Learning – IDEAL 2018, H. Yin, et al., eds., Lecture Notes in Computer Science, vol. 11314, Cham: Springer International Publishing, 2018, pp.508-519.
Meyer, S., Bertrand, O.J.N., Egelhaaf, M., Hammer, B.: Inferring Temporal Structure from Predictability in Bumblebee Learning Flight. In: Yin, H., Camacho, D., Novais, P., and Tallón-Ballesteros, A.J. (eds.) Intelligent Data Engineering and Automated Learning – IDEAL 2018. Lecture Notes in Computer Science. 11314, p. 508-519. Springer International Publishing, Cham (2018).
Meyer, Stefan, Bertrand, Olivier J. N., Egelhaaf, Martin, and Hammer, Barbara. “Inferring Temporal Structure from Predictability in Bumblebee Learning Flight”. Intelligent Data Engineering and Automated Learning – IDEAL 2018. Ed. Hujun Yin, David Camacho, Paul. Novais, and Antonio J. Tallón-Ballesteros. Cham: Springer International Publishing, 2018.Vol. 11314. Lecture Notes in Computer Science. 508-519.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Suchen in

Google Scholar
ISBN Suche