Behrens et al. found that humans take into account the volatility of reward probabilities in a reinforcement learning task.
The way they took the volatility into account was qualitatively modelled by a Bayesian learner.⇒
Kleesiek et al. introduce adaptive learning rates to RNNPB which results in faster and more stable training.⇒
RNNPB learns sequences of inputs unsupervised (self-organized).⇒