RT Journal Article
T1 Fast social-like learning of complex behaviors based on motor motifs
A1 Calvo Tapia, Carlos
A1 Tyukin, Ivan
A1 Makarov Slizneva, Valeriy
AB Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a complex behavior can be decomposed into a sequence of n motor motifs. Then a neural network capable of activating motor motifs in a given sequence can drive an agent. To account for (n − 1)! possible sequences of motifs in a neural network, we employ the winnerless competition approach. We then consider a teacher-learner situation: one agent exhibits a complex movement, while another one aims at mimicking the teacher’s behavior. Despite the huge variety of possible motif sequences we show that the learner, equipped with the provided learning model, can rewire “on the fly” its synaptic couplings in no more than (n − 1) learning cycles and converge exponentially to the durations of the teacher’s motifs. We validate the learning model on mobile robots. Experimental results show that the learner is indeed capable of copying the teacher’s behavior composed of six motor motifs in a few learning cycles. The reported mechanism of learning is general and can be used for replicating different functions, including, for example, sound patterns or speech.
PB American Physical Society
SN 2470-0045
YR 2018
FD 2018
LK https://hdl.handle.net/20.500.14352/96140
UL https://hdl.handle.net/20.500.14352/96140
LA eng
NO Calvo Tapia C, Tyukin IY, Makarov VA. Fast social-like learning of temporal patterns in neural networks. Physical Review E 97(5) 052308, 2018
NO Russian Science Foundation 
NO Ministerio de Economía y Competitividad (España)
DS Docta Complutense
RD 19 dic 2025