161 citations · 528 across the 21 of their papers we have counts for
9 papers · 1 filter
Designing Ecosystems of Intelligence from First Principles
Karl J Friston, Maxwell J D Ramstead, Alex B Kiefer +17
This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosyste…
Path integrals, particular kinds, and strange things
Karl Friston, Lancelot Da Costa, Dalton A. R. Sakthivadivel +4
This paper describes a path integral formulation of the free energy principle. The ensuing account expresses the paths or trajectories that a particle takes as it evolves over time…
Knitting a Markov blanket is hard when you are out-of-equilibrium: two examples in canonical nonequilibrium models
Miguel Aguilera, Ángel Poc-López, Conor Heins +1
Bayesian theories of biological and brain function speculate that Markov blankets (a conditional independence separating a system from external states) play a key role for facilita…
Spin glass systems as collective active inference
Conor Heins, Brennan Klein, Daphne Demekas +2
An open question in the study of emergent behaviour in multi-agent Bayesian systems is the relationship, if any, between individual and collective inference. In this paper we explo…
Sparse coupling and Markov blankets: A comment on "How particular is the physics of the Free Energy Principle?" by Aguilera, Millidge, Tschantz and Buckley
Conor Heins, Lancelot Da Costa
In this commentary, we respond to a technical analysis of the Free Energy Principle (hereafter: FEP) presented in "How particular is the physics of the Free Energy Principle" by Ag…
Particular flows and attracting sets: A comment on "How particular is the physics of the Free Energy Principle?" by Aguilera, Millidge, Tschantz and Buckley
Conor Heins
In this commentary, I expand on the analysis of the recent article "How particular is the physics of the Free Energy Principle?" by Aguilera et al. by studying the flow fields of l…
On Bayesian Mechanics: A Physics of and by Beliefs
Maxwell J. D. Ramstead, Dalton A. R. Sakthivadivel, Conor Heins +5
The aim of this paper is to introduce a field of study that has emerged over the last decade called Bayesian mechanics. Bayesian mechanics is a probabilistic mechanics, comprising…
The free energy principle made simpler but not too simple
Karl Friston, Lancelot Da Costa, Noor Sajid +4
This paper provides a concise description of the free energy principle, starting from a formulation of random dynamical systems in terms of a Langevin equation and ending with a Ba…
pymdp: A Python library for active inference in discrete state spaces
Conor Heins, Beren Millidge, Daphne Demekas +4
Active inference is an account of cognition and behavior in complex systems which brings together action, perception, and learning under the theoretical mantle of Bayesian inferenc…