231 citations · 828 across the 31 of their papers we have counts for
4 papers · 1 filter
Branching Time Active Inference: the theory and its generality
Théophile Champion, Lancelot Da Costa, Howard Bowman +1
Over the last 10 to 15 years, active inference has helped to explain various brain mechanisms from habit formation to dopaminergic discharge and even modelling curiosity. However,…
Active inference, Bayesian optimal design, and expected utility
Noor Sajid, Lancelot Da Costa, Thomas Parr +1
Active inference, a corollary of the free energy principle, is a formal way of describing the behavior of certain kinds of random dynamical systems that have the appearance of sent…
Bayesian brains and the Rényi divergence
Noor Sajid, Francesco Faccio, Lancelot Da Costa +3
Under the Bayesian brain hypothesis, behavioural variations can be attributed to different priors over generative model parameters. This provides a formal explanation for why indiv…
Bayesian Mechanics for Stationary Processes
Lancelot Da Costa, Karl Friston, Conor Heins +1
This paper develops a Bayesian mechanics for adaptive systems. Firstly, we model the interface between a system and its environment with a Markov blanket. This affords conditions u…