TY - GEN
T1 - Spiking neural network controllers evolved for animat foraging based on temporal pattern recognition in the presence of noise on input
AU - Bensmail, Chama
AU - Steuber, Volker
AU - Davey, Neil
AU - Wróbel, Borys
N1 - © Springer Nature Switzerland AG 2018
PY - 2018/9/27
Y1 - 2018/9/27
N2 - We evolved spiking neural network controllers for simple animats, allowing for these networks to change topologies and weights during evolution. The animats’ task was to discern one correct pattern (emitted from target objects) amongst other different wrong patterns (emitted from distractor objects), by navigating towards targets and avoiding distractors in a 2D world. Patterns were emitted with variable silences between signals of the same pattern in the attempt of creating a state memory. We analyse the network that is able to accomplish the task perfectly for patterns consisting of two signals, with 4 interneurons, maintaining its state (although not infinitely) thanks to the recurrent connections.
AB - We evolved spiking neural network controllers for simple animats, allowing for these networks to change topologies and weights during evolution. The animats’ task was to discern one correct pattern (emitted from target objects) amongst other different wrong patterns (emitted from distractor objects), by navigating towards targets and avoiding distractors in a 2D world. Patterns were emitted with variable silences between signals of the same pattern in the attempt of creating a state memory. We analyse the network that is able to accomplish the task perfectly for patterns consisting of two signals, with 4 interneurons, maintaining its state (although not infinitely) thanks to the recurrent connections.
KW - Adaptive exponential integrate and fire
KW - Animat
KW - Spiking neural networks
KW - Temporal pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=85054813240&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-01418-6_30
DO - 10.1007/978-3-030-01418-6_30
M3 - Conference contribution
AN - SCOPUS:85054813240
SN - 9783030014179
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 304
EP - 313
BT - Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018, Proceedings
PB - Springer Nature
T2 - 27th International Conference on Artificial Neural Networks, ICANN 2018
Y2 - 4 October 2018 through 7 October 2018
ER -