Artificial neural networks (ANNs) have emerged as an essential tool in
m...
We describe a parametrized space for simple meta-reinforcement-learning
...
In meta-learning, networks are trained with external algorithms to learn...
Deep learning networks generally use non-biological learning methods. By...
Continual learning is the problem of sequentially learning new tasks or
...
The impressive lifelong learning in animal brains is primarily enabled b...
Continual lifelong learning requires an agent or model to learn many
seq...
In this paper, we introduce a novel form of value function, Q(s, s'), th...
Standard gradient descent methods are susceptible to a range of issues t...
How can we build agents that keep learning from experience, quickly and
...
Various measures can be used to estimate bias or unfairness in a predict...
Hebbian plasticity is a powerful principle that allows biological brains...
While gradient descent has proven highly successful in learning connecti...