On the dynamics of small continuous-time recurrent neural networks
Adaptive Behavior - Special issue on computational neuroethology
Evolutionary robotics and the radical envelope-of-noise hypothesis
Adaptive Behavior
Minimal agency detection of embodied agents
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Neural uncertainty and sensorimotor robustness
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
| Hi-index | 0.00 |
Continuous-time recurrent neural networks affected by random additive noise are evolved to produce phototactic behaviour in simulated mobile agents. The resulting neurocontrollers are evaluated after evolution against perturbations and for different levels of neural noise. Controllers evolved with neural noise are more robust and may still function in the absence of noise. Evidence from behavioural tests indicates that robust controllers do not undergo noise-induced bifurcations or if they do, the transient dynamics remain functional. A general hypothesis is proposed according to which evolution implicitly selects neural systems that operate in noise-resistant landscapes which are hard to bifurcate and/or bifurcate while retaining functionality.