Applying the Free Energy Principle to Complex Adaptive Systems
The article discusses the Free Energy Principle (FEP) as a unified model for understanding adaptive behaviors in complex systems, extending beyond the…
Tag: 2022
A Probabilistic Generative Model of Free Categories
This paper presents a probabilistic generative model for morphisms in free monoidal categories, linking applied category theory and machine learning. …
Towards a geometry and analysis for Bayesian mechanics
The paper formulates Bayesian mechanics via axiomatic principles, arguing that constrained dynamical systems infer against these constraints, implying…
Embodied object representation learning and recognition
The article discusses a novel approach to object recognition and representation learning, emphasizing the importance of interactive learning, akin to …
Stress and its sequelae: An active inference account of the etiological pathway from allostatic overload to depression
The paper discusses how stress induces physiological changes that lead to a loss of predictive confidence, resulting in depression. It uses the active…
Active inference models do not contradict folk psychology
Active inference presents a cohesive theory of perception, learning, and decision-making. The authors address concerns about its compatibility with fo…
Epistemic communities under active inference
The paper explores the dynamics of information spread and confirmation bias within epistemic communities using an active inference model. It reveals h…
From generative models to generative passages: a computational approach to (neuro) phenomenology
This paper introduces a generative modelling approach to neurophenomenology, merging computational neuroscience with phenomenological philosophy. It r…
Action and Perception as Divergence Minimization – original publication September 3, 2020
The paper introduces Action Perception Divergence (APD), a framework for categorizing objective functions in intelligent agents. It distinguishes betw…
Why Bayesian brains perform poorly on explicit probabilistic reasoning problems
The paper explores why Bayesian inference in the brain contributes to poor performance on explicit probabilistic reasoning tasks. It distinguishes bet…