The use of deep neural networks in reinforcement learning (RL) often suffers from
performance degradation as model size increases. While soft mixtures of experts (SoftMoEs) …

We develop a methodology that employs mixture of experts to scale up the parameters of
reinforcement learning (RL) models in optimal execution tasks. The innovation of our …

We consider the problem of optimally composing a set of primitives to tackle control tasks. To
address this problem, we introduce Neo-FREE: a control architecture inspired by the …