We propose an artificial life framework aimed at facilitating the emerge...
In reinforcement learning, we can learn a model of future observations a...
When agents interact with a complex environment, they must form and main...
We describe TF-Replicator, a framework for distributed machine learning
...
Natural language processing has made significant inroads into learning t...
We propose a formulation of visual localization that does not require
co...
One motivation for learning generative models of environments is to use ...
A key challenge in model-based reinforcement learning (RL) is to synthes...
In this work we introduce a differentiable version of the Compositional
...
We introduce a simple recurrent variational auto-encoder architecture th...