2 citations · 3 across the 3 of their papers we have counts for
3 papers
Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning
Théophile Champion, Marek Grześ, Howard Bowman
Model-based reinforcement learning refers to a set of approaches capable of sample-efficient decision making, which create an explicit model of the environment. This model can subs…
Reframing the Expected Free Energy: Four Formulations and a Unification
Théophile Champion, Howard Bowman, Dimitrije Marković +1
Active inference is a leading theory of perception, learning and decision making, which can be applied to neuroscience, robotics, psychology, and machine learning. Active inference…
Realising Active Inference in Variational Message Passing: the Outcome-blind Certainty Seeker
Théophile Champion, Marek Grześ, Howard Bowman
Active inference is a state-of-the-art framework in neuroscience that offers a unified theory of brain function. It is also proposed as a framework for planning in AI. Unfortunatel…