MiG

Conditioned behavior in a robot controlled by a spiking neural network

Raúl Rojas, Tim Landgraf, Martin Nawrot, Lovisa Irpa Helgadottir, Joachim Haenicke— 2013

Insects show a rich repertoire of goal-directed and adaptive behaviors that are still beyond the capabilities of today's artificial systems. Fast progress in our comprehension of the underlying neural computations make the insect a favorable model system for neurally inspired computing paradigms in autonomous robots. Here, we present a robotic platform designed for implementing and testing spiking neural network control architectures. We demonstrate a neuromorphic realtime approach to sensory processing, reward-based associative plasticity and behavioral control. This is inspired by the biological mechanisms underlying rapid associative learning and the formation of distributed memories in the insect.

TitelConditioned behavior in a robot controlled by a spiking neural network
VerfasserRaúl Rojas, Tim Landgraf, Martin Nawrot, Lovisa Irpa Helgadottir, Joachim Haenicke
VerlagIEEE Xplore
Datum201311
KennungDOI: 10.1109/NER.2013.6696078; ISSN: 1948-3546
Quelle/n
Erschienen inProceedings of the 6th IEEE/EMBS Conference on Neural Engineering (NER), November 2013
Größe oder Länge891-894