L
Lancelot Da Costa
Researcher at Imperial College London
Publications - 32
Citations - 651
Lancelot Da Costa is an academic researcher from Imperial College London. The author has contributed to research in topics: Inference & Computer science. The author has an hindex of 7, co-authored 20 publications receiving 256 citations. Previous affiliations of Lancelot Da Costa include UCL Institute of Neurology & University College London.
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Journal ArticleDOI
Active inference on discrete state-spaces: A synthesis.
Lancelot Da Costa,Lancelot Da Costa,Thomas Parr,Noor Sajid,Sebastijan Veselic,Victorita Neacsu,Karl J. Friston +6 more
TL;DR: A complete mathematical synthesis of active inference on discrete state-space models, which derives neuronal dynamics from first principles and relates this dynamics to biological processes is provided.
Journal ArticleDOI
Markov blankets, information geometry and stochastic thermodynamics
TL;DR: There is a natural Bayesian mechanics for any system that possesses a Markov blanket, which means that there is an explicit link between the inference performed by internal states and their energetics—as characterized by their stochastic thermodynamics.
Posted Content
Sophisticated Inference.
TL;DR: A sophisticated kind of active inference using a recursive form of expected free energy, which effectively implements a deep tree search over actions and outcomes in the future over sequences of belief states as opposed to states per se.
Journal ArticleDOI
Active inference on discrete state-spaces: a synthesis
Lancelot Da Costa,Thomas Parr,Noor Sajid,Sebastijan Veselic,Victorita Neacsu,Karl J. Friston +5 more
TL;DR: In this article, a complete mathematical synthesis of active inference on discrete state-space models is provided, which can be used as a practical guide on how to implement active inference to simulate experimental behaviour, or a pointer towards various in-silico neurophysiological responses that may be used to make empirical predictions.
Journal ArticleDOI
Some interesting observations on the free energy principle
TL;DR: This discussion focuses on solenoidal coupling between various states in sparsely coupled systems that possess a Markov blanket - and the distinction between exact and approximate Bayesian inference, implied by the ensuing Bayesian mechanics.