119 citations · 515 across the 60 of their papers we have counts for
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Active Inference in Robotics and Artificial Agents: Survey and Challenges
Pablo Lanillos, Cristian Meo, Corrado Pezzato +8
Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning. Recently, it ha…
A Mathematical Walkthrough and Discussion of the Free Energy Principle
Beren Millidge, Anil Seth, Christopher L Buckley
The Free-Energy-Principle (FEP) is an influential and controversial theory which postulates a deep and powerful connection between the stochastic thermodynamics of self-organizatio…
Habitual and Reflective Control in Hierarchical Predictive Coding
Paul F. Kinghorn, Beren Millidge, Christopher L. Buckley
In cognitive science, behaviour is often separated into two types. Reflexive control is habitual and immediate, whereas reflective is deliberative and time consuming. We examine th…
Predictive Coding: a Theoretical and Experimental Review
Beren Millidge, Anil Seth, Christopher L Buckley
Predictive coding offers a potentially unifying account of cortical function -- postulating that the core function of the brain is to minimize prediction errors with respect to a g…
Applications of the Free Energy Principle to Machine Learning and Neuroscience
Beren Millidge
In this PhD thesis, we explore and apply methods inspired by the free energy principle to two important areas in machine learning and neuroscience. The free energy principle is a g…
Towards a Mathematical Theory of Abstraction
Beren Millidge
While the utility of well-chosen abstractions for understanding and predicting the behaviour of complex systems is well appreciated, precisely what an abstraction has…
Online reinforcement learning with sparse rewards through an active inference capsule
Alejandro Daniel Noel, Charel van Hoof, Beren Millidge
Intelligent agents must pursue their goals in complex environments with partial information and often limited computational capacity. Reinforcement learning methods have achieved g…
How particular is the physics of the free energy principle?
Miguel Aguilera, Beren Millidge, Alexander Tschantz +1
The free energy principle (FEP) states that any dynamical system can be interpreted as performing Bayesian inference upon its surrounding environment. In this work, we examine in d…
Understanding the Origin of Information-Seeking Exploration in Probabilistic Objectives for Control
Beren Millidge, Anil Seth, Christopher Buckley
The exploration-exploitation trade-off is central to the description of adaptive behaviour in fields ranging from machine learning, to biology, to economics. While many approaches…
Neural Kalman Filtering
Beren Millidge, Alexander Tschantz, Anil Seth +1
The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a previous state estimate, and a dynamics model to produce a principled estimate of the curren…