activity
20232026
most citedAutomating Model Comparison in Factor Graphs

1 citations · 1 across the 12 of their papers we have counts for

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cs.AI2026

Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification

Karim Zaghw, Andrew Pashea, Marc Pritsch +3

Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and temporal domains remains difficul…

cs.AI2026

Sophisticated Policies from Epistemic Priors

Wouter W. L. Nuijten, Bert de Vries

Sophisticated Inference is a variant of active inference often associated with recursive belief modeling and tree search. We argue that its central computational role is simpler: w…

cs.AI2026

What Type of Inference is Active Inference?

Wouter W. L. Nuijten, Mykola Lukashchuk, Thijs van de Laar +1

Active inference casts decision-making as inference, with the Expected Free Energy (EFE) unifying goal-directed and information-seeking behavior. Recent work showed that EFE minimi…

cs.AI2026

Expected Free Energy-based Planning as Variational Inference

Wouter W. L. Nuijten, Thijs van de Laar, Bert de Vries

Planning under uncertainty requires agents to balance goal achievement with information gathering. Active inference addresses this through the Expected Free Energy (EFE), a cost fu…

cs.AI2025

Active Inference is a Subtype of Variational Inference

Wouter W. L. Nuijten, Mykola Lukashchuk

Automated decision-making under uncertainty requires balancing exploitation and exploration. Classical methods treat these separately using heuristics, while Active Inference unifi…

cs.AI2025

Message passing-based inference in an autoregressive active inference agent

Wouter M. Kouw, Tim N. Nisslbeck, Wouter L. N. Nuijten

We present the design of an autoregressive active inference agent in the form of message passing on a factor graph. Expected free energy is derived and distributed across a plannin…