37 citations · 107 across the 10 of their papers we have counts for
12 papers
Knitting a Markov blanket is hard when you are out-of-equilibrium: two examples in canonical nonequilibrium models
Miguel Aguilera, Ángel Poc-López, Conor Heins +1
Bayesian theories of biological and brain function speculate that Markov blankets (a conditional independence separating a system from external states) play a key role for facilita…
Spin glass systems as collective active inference
Conor Heins, Brennan Klein, Daphne Demekas +2
An open question in the study of emergent behaviour in multi-agent Bayesian systems is the relationship, if any, between individual and collective inference. In this paper we explo…
Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model
Miguel Aguilera, Masanao Igarashi, Hideaki Shimazaki
Most natural systems operate far from equilibrium, displaying time-asymmetric, irreversible dynamics characterized by a positive entropy production while exchanging energy and matt…
Inference in neural networks using conditional mean-field methods
Ángel Poc-López, Miguel Aguilera
We extend previous mean-field approaches for non-equilibrium neural network models to estimate correlations in the system. This offers a powerful tool for approximating the system…
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…
A unifying framework for mean-field theories of asymmetric kinetic Ising systems
Miguel Aguilera, S. Amin Moosavi, Hideaki Shimazaki
Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods…
Integrated information in the thermodynamic limit
Miguel Aguilera, Ezequiel Di Paolo
The capacity to integrate information is a prominent feature of biological and cognitive systems. Integrated Information Theory (IIT) provides a mathematical approach to quantify t…
Integrated Information and Autonomy in the Thermodynamic Limit
Miguel Aguilera, Ezequiel Di Paolo
The concept of autonomy is fundamental for understanding biological organization and the evolutionary transitions of living systems. Understanding how a system constitutes itself a…
Adaptation to criticality through organizational invariance in embodied agents
Miguel Aguilera, Manuel G. Bedia
Many biological and cognitive systems do not operate deep within one or other regime of activity. Instead, they are poised at critical points located at phase transitions in their…
Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents
Miguel Aguilera, Manuel G. Bedia
This paper outlines a methodological approach for designing adaptive agents driving themselves near points of criticality. Using a synthetic approach we construct a conceptual mode…
Learning Criticality in an Embodied Boltzmann Machine
Miguel Aguilera, Manuel G. Bedia
Many biological and cognitive systems do not operate deep into one or other regime of activity. Instead, they exploit critical surfaces poised at transitions in their parameter spa…
Rhythms of the collective brain: Metastable synchronization and cross-scale interactions in connected multitudes
Miguel Aguilera
Crowd behaviour challenges our fundamental understanding of social phenomena. Involving complex interactions between multiple temporal and spatial scales of activity, its governing…