Intra-Active Inference I: Fundamentals
This paper, the first in a series, explores the application of new materialism to the free energy principle (FEP). It highlights the interplay between…
Category: Scientific Research Papers
Active Inference in Hebbian Learning Networks
This research explores active inference using brain-inspired Hebbian learning networks to control agents. It describes a dual-network system that lear…
Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making
The paper explores the development of explainable AI systems using active inference, emphasizing transparency in decision-making and introspection. It…
Realising Synthetic Active Inference Agents, Part II: Variational Message Updates
This paper continues the exploration of synthetic Active Inference (AIF) agents as detailed in Part I, focusing on variational message updates. It hig…
On Embedded Normativity-An Active Inference account of agency beyond flesh
The paper introduces "embedded normativity" within the Active Inference framework, proposing that social norms emerge through human interaction with t…
Fusing event-based camera and radar for SLAM using spiking neural networks with continual STDP learning
The study introduces a novel SLAM architecture combining event-based cameras and FMCW radar for drone navigation, utilizing bio-inspired Spiking Neura…
Computing with Categories in Machine Learning
The paper introduces DisCoPyro, a framework combining category theory with amortized variational inference for machine learning. It bridges the gap be…
The free energy principle made simpler but not too simple – original pub date – Jan 17, 2022
The paper elucidates the free energy principle, linking random dynamical systems to Bayesian mechanics as a framework for understanding sentience. It …
String Diagrams with Factorized Densities
The work by Eli Sennesh and Jan-Willem van de Meent explores probabilistic programs and causal models, emphasizing compositionally reasoning about mod…
FMCW Radar Sensing for Indoor Drones Using Variational Auto-Encoders
This paper explores using variational auto-encoders to learn low-dimensional representations from FMCW radar data for indoor drone navigation. It intr…