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Many of the mathematical frameworks describing natural selection are equivalent to Bayes Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude…

General Physics · Physics 2016-06-28 John O. Campbell

Bayes' theorem incorporates distinct types of information through the likelihood and prior. Direct observations of state variables enter the likelihood and modify posterior probabilities through consistent updating. Information in terms of…

Methodology · Statistics 2024-07-19 Duncan K. Foley , Ellis Scharfenaker

The theory of evolution by natural selection cannot be used to evaluate the truth value of the following proposition: Through evolution, there exists at least one species that can adapt to any one given environment. To address this issue,…

Biological Physics · Physics 2022-08-17 Kai Xu

This paper provides a concise description of the free energy principle, starting from a formulation of random dynamical systems in terms of a Langevin equation and ending with a Bayesian mechanics that can be read as a physics of sentience.…

The theory of natural selection has two forms. Deductive theory describes how populations change over time. One starts with an initial population and some rules for change. From those assumptions, one calculates the future state of the…

Populations and Evolution · Quantitative Biology 2016-11-15 Steven A. Frank

Organisms are nonequilibrium, stationary systems self-organized via spontaneous symmetry breaking and undergoing metabolic cycles with broken detailed balance in the environment. The thermodynamic free-energy principle describes an…

Neurons and Cognition · Quantitative Biology 2022-11-24 Chang Sub Kim

Genetic information and environmental factors determine the path of an individuals life and therefore, the evolution of its entire species. We have succeeded in proposing and studying a model that captures this idea. In our model, a…

Populations and Evolution · Quantitative Biology 2021-07-28 N. Abadi , G. Abramson

Every interaction of a living organism with its environment involves the placement of a bet. Armed with partial knowledge about a stochastic world, the organism must decide its next step or near-term strategy, an act that implicitly or…

Populations and Evolution · Quantitative Biology 2023-05-30 Philipp Fleig , Vijay Balasubramanian

It is a common belief that in any environment where life is possible, life will be generated. Here it is suggested that the cause for a spontaneous generation of complex systems is probability driven processes. Based on equilibrium…

Information Theory · Computer Science 2007-11-29 Oded Kafri

In this paper, a simple case of Bayesian mechanics under the free energy principle is formulated in axiomatic terms. We argue that any dynamical system with constraints on its dynamics necessarily looks as though it is performing inference…

Mathematical Physics · Physics 2022-04-27 Dalton A R Sakthivadivel

Behavior in the context of game theory is described as a natural process that follows the 2nd law of thermodynamics. The rate of entropy increase as the payoff function is derived from statistical physics of open systems. The thermodynamic…

General Physics · Physics 2011-10-27 Jani Anttila , Arto Annila

We develop a novel data-driven approach to the inverse problem of classical statistical mechanics: given experimental data on the collective motion of a classical many-body system, how does one characterise the free energy landscape of that…

Statistical Mechanics · Physics 2022-03-01 Peter Yatsyshin , Serafim Kalliadasis , Andrew B. Duncan

How do organisms recognize their environment by acquiring knowledge about the world, and what actions do they take based on this knowledge? This article examines hypotheses about organisms' adaptation to the environment from machine…

Neurons and Cognition · Quantitative Biology 2019-03-01 Hideaki Shimazaki

Statistical Inference is the process of determining a probability distribution over the space of parameters of a model given a data set. As more data becomes available this probability distribution becomes updated via the application of…

Disordered Systems and Neural Networks · Physics 2022-04-28 David S. Berman , Jonathan J. Heckman , Marc Klinger

The equations of evolutionary change by natural selection are commonly expressed in statistical terms. Fisher's fundamental theorem emphasizes the variance in fitness. Quantitative genetics expresses selection with covariances and…

Populations and Evolution · Quantitative Biology 2012-11-20 Steven A. Frank

This article reviews how organisms learn and recognize the world through the dynamics of neural networks from the perspective of Bayesian inference, and introduces a view on how such dynamics is described by the laws for the entropy of…

Neurons and Cognition · Quantitative Biology 2020-06-24 Hideaki Shimazaki

A government has to finance a risk for its population. It shares the charges among the population with a fixed scale based on economic criteria. Various organisms have to collect and to redistribute fairly the subsidies. Under these…

General Finance · Quantitative Finance 2014-01-14 Guy Cirier

A common assumption in evolutionary thought is that adaptation drives an increase in biological complexity. However, the rules governing evolution of complexity appear more nuanced. Evolution is deeply connected to learning, where…

Populations and Evolution · Quantitative Biology 2025-08-06 Hagai Rappeport , Mor Nitzan

The aim of this paper is to introduce a field of study that has emerged over the last decade called Bayesian mechanics. Bayesian mechanics is a probabilistic mechanics, comprising tools that enable us to model systems endowed with a…

In statistical thermodynamics the 2nd law is properly spelled out in terms of conditioned probabilities. As such it makes the statement, that `entropy increases with time' without preferring a time direction. In this paper I try to explain…

General Physics · Physics 2022-06-27 Domenico Giulini
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