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. The …
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 …
Recent advances in neuroscience have characterised brain function using mathematical formalisms and first principles that may be usefully applied elsewhere. In this paper, we …
In this paper, we explore the known connection among sustainability, resilience, and well- being within the framework of active inference. Initially, we revisit how the notions of well …
Active inference is a probabilistic framework for modeling the behavior of biological and artificial agents, which derives from the principle of minimizing free energy. In recent years …
L Da Costa, GA Pavliotis - Journal of Physics A: Mathematical …, 2023 - iopscience.iop.org
The entropy production rate is a central quantity in non-equilibrium statistical physics, scoring how far a stochastic process is from being time-reversible. In this paper, we compute …
DAR Sakthivadivel - International Workshop on Active Inference, 2022 - Springer
Bayesian mechanics is a new approach to studying the mathematics and physics of interacting stochastic processes. We provide a worked example of a physical mechanics for …
DAR Sakthivadivel - arXiv preprint arXiv:2205.07793, 2022 - arxiv.org
In a recent technical critique of the free energy principle (FEP) due to Aguilera-Millidge- Tschantz-Buckley, it is argued that there are a number of instances where the FEP $\unicode …
R Wei - arXiv preprint arXiv:2408.06542, 2024 - arxiv.org
Expected free energy (EFE) is a central quantity in active inference which has recently gained popularity due to its intuitive decomposition of the expected value of control into a …