On Bayesian mechanics: a physics of and by beliefs

Interface Focus, Journal Year: 2023, Volume and Issue: 13(3)

Published: April 14, 2023

The aim of this paper is to introduce a field study that has emerged over the last decade, called Bayesian mechanics. mechanics probabilistic mechanics, comprising tools enable us model systems endowed with particular partition (i.e. into particles), where internal states (or trajectories states) system encode parameters beliefs about external their trajectories). These allow write down mechanical theories for look as if they are estimating posterior probability distributions causes sensory states. This provides formal language modelling constraints, forces, potentials and other quantities determining dynamics such systems, especially entail on space statistical manifold). Here, we will review state art in literature free energy principle, distinguishing between three ways which been applied path-tracking, mode-tracking mode-matching). We go examine duality principle constrained maximum entropy both lie at heart discuss its implications.

Language: Английский

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How Active Inference Could Help Revolutionise Robotics

Entropy, Journal Year: 2022, Volume and Issue: 24(3), P. 361 - 361

Published: March 2, 2022

Recent advances in neuroscience have characterised brain function using mathematical formalisms and first principles that may be usefully applied elsewhere. In this paper, we explain how active inference—a well-known description of sentient behaviour from neuroscience—can exploited robotics. short, inference leverages the processes thought to underwrite human build effective autonomous systems. These systems show state-of-the-art performance several robotics settings; highlight these framework used advance

Language: Английский

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Knowledge Graphs (KG) Assisted Variational Autoencoder (VAE) for Large-Scale Anomaly and Event Detection

Lecture notes in computer science, Journal Year: 2025, Volume and Issue: unknown, P. 199 - 214

Published: Jan. 1, 2025

Language: Английский

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Sustainability under Active Inference

Published: May 2, 2024

In this paper we explore the known connection among sustainability, resilience, and well-being within framework of active inference. Initially, revisit how notions resilience intersect inference before defining sustainability. We adopt a holistic concept sustainability denoting enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth encompass community networks, labor, knowledge. Using Free Energy Principle, can emphasize role fostering resource renewal, harmonious system-entity exchanges, practices that encourage self-organization as pathways achieving both in an agent collectives. start by connecting Active Inference with well-being, building on exsiting work. then attempt link asserting alone is insufficient for sustainable outcomes. While absorbing shocks stresses, must be intrinsically linked ensure adaptive capacities do not merely perpetuate existing vulnerabilities. Rather, it should facilitate transformative processes address root causes unsustainability. Sustainability, therefore, manifest across extended timescales all system strata, from individual components broader system, uphold ecological integrity, economic stability, social well-being. explain manifests at level agent, collectives systems. To model quantify interdependencies between resources their impact overall introduce application network theory dynamical systems theory. optimization precision or learning rates through framework, advocating approach fosters elastic plastic necessary long-term abundance.

Language: Английский

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Sustainability under Active Inference

Systems, Journal Year: 2024, Volume and Issue: 12(5), P. 163 - 163

Published: May 4, 2024

In this paper, we explore the known connection among sustainability, resilience, and well-being within framework of active inference. Initially, revisit how notions resilience intersect inference before defining sustainability. We adopt a holistic concept sustainability denoting enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth encompass community networks, labor, knowledge. Using free energy principle, can emphasize role fostering resource renewal, harmonious system–entity exchanges, practices that encourage self-organization as pathways achieving both an agent part collective. start by connecting with well-being, building on existing work. then attempt link asserting alone is insufficient for sustainable outcomes. While absorbing shocks stresses, must be intrinsically linked ensure adaptive capacities do not merely perpetuate vulnerabilities. Rather, it should facilitate transformative processes address root causes unsustainability. Sustainability, therefore, manifest across extended timescales all system strata, from individual components broader system, uphold ecological integrity, economic stability, social well-being. explain manifests at level collectives systems. To model quantify interdependencies between resources their impact overall introduce application network theory dynamical systems theory. optimization precision or learning rates through framework, advocating approach fosters elastic plastic necessary long-term abundance.

Language: Английский

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A Worked Example of the Bayesian Mechanics of Classical Objects

Communications in computer and information science, Journal Year: 2023, Volume and Issue: unknown, P. 298 - 318

Published: Jan. 1, 2023

Language: Английский

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The entropy production of stationary diffusions

Journal of Physics A Mathematical and Theoretical, Journal Year: 2023, Volume and Issue: 56(36), P. 365001 - 365001

Published: June 19, 2023

Abstract The entropy production rate is a central quantity in non-equilibrium statistical physics, scoring how far stochastic process from being time-reversible. In this paper, we compute the of diffusion processes at steady-state under condition that time-reversal remains diffusion. We start by characterising both discrete and continuous-time Markov processes. investigate time-homogeneous stationary diffusions recall most general conditions for reversibility property, which includes hypoelliptic degenerate diffusions, locally Lipschitz vector fields. decompose drift into its time-reversible irreversible parts, or equivalently, generator symmetric antisymmetric operators. show equivalence with decomposition backward Kolmogorov equation considered hypocoercivity theory, Fokker-Planck GENERIC form. main result shows when time-irreversible part range volatility matrix (almost everywhere) forward time-reversed path space measures are mutually equivalent, evaluates production. When does not hold, singular infinite. verify these results using exact numerical simulations linear diffusions. illustrate discrepancy between non-linear their several examples can be used accurate simulation. Finally, discuss relationship time-irreversibility sampling efficiency, modify definition to score generalised reversible.

Language: Английский

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Nesterov Smoothing for Sampling Without Smoothness

Published: Dec. 13, 2023

We study the problem of sampling from a target distribution in $\mathbb{R}^{d}$ whose potential is not smooth. Compared with smooth potentials, this much less well-understood due to lack smoothness. In paper, we propose novel algorithm for class non-smooth potentials by first approximating them using technique that akin Nesterov smoothing. then utilize algorithms on generate approximate samples original potentials. select an appropriate smoothing intensity ensure distance between smoothed and un-smoothed distributions minimal, thereby guaranteeing algorithm's accuracy. Hence obtain non-asymptotic convergence results based existing analysis sampling. verify our result synthetic example apply method improve worst-case performance Bayesian inference real-world example.

Language: Английский

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