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Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics…

Other Quantitative Biology · Quantitative Biology 2018-02-26 Mikhail I. Katsnelson , Yuri I. Wolf , Eugene V. Koonin

Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability,…

Neurons and Cognition · Quantitative Biology 2024-07-02 James Malkin , Cian O'Donnell , Conor Houghton , Laurence Aitchison

Non-equilibrium thermodynamics has long been an area of substantial interest to ecologists because most fundamental biological processes, such as protein synthesis and respiration, are inherently energy-consuming. Microbial communities are…

Populations and Evolution · Quantitative Biology 2022-01-19 Jacob Cook , Samraat Pawar , Robert G. Endres

In a previous paper, we introduced an axiomatic system for information thermodynamics, deriving an entropy function that includes both thermodynamic and information components. From this function we derived an entropic probability…

Quantum Physics · Physics 2024-12-18 Benjamin Schumacher , Michael D. Westmoreland

The inheritance of characteristics induced by the environment has often been opposed to the theory of evolution by natural selection. Yet, while evolution by natural selection requires new heritable traits to be produced and transmitted, it…

Populations and Evolution · Quantitative Biology 2015-06-18 Olivier Rivoire , Stanislas Leibler

We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model where agents who make decisions using either automatic or…

Dynamical Systems · Mathematics 2015-07-07 Danielle F. P. Toupo , Steven H. Strogatz , Jonathan D. Cohen , David G. Rand

Natural phenomenon of coevolution is the reciprocally induced evolutionary change between two or more species or population. Though this biological occurrence is a natural fact, there are only few attempts to use this as a simile in…

Other Computer Science · Computer Science 2012-06-07 Siby Abraham , Sugata Sanyal , Mukund Sanglikar

Bayesian models of behavior have provided computational level explanations in a range of psychophysical tasks. One fundamental experimental paradigm is the production or reproduction task, in which subjects are instructed to generate an…

Machine Learning · Computer Science 2022-01-03 Nils Neupärtl , Constantin A. Rothkopf

The problem of making sequential decisions in unknown probabilistic environments is studied. In cycle $t$ action $y_t$ results in perception $x_t$ and reward $r_t$, where all quantities in general may depend on the complete history. The…

Artificial Intelligence · Computer Science 2007-05-23 Marcus Hutter

Sweepstakes reproduction may be generated by chance matching of reproduction with favorable environmental conditions. Gene genealogies generated by sweepstakes reproduction are in the domain of attraction of multiple-merger coalescents…

Probability · Mathematics 2026-01-15 Bjarki Eldon

The quest to comprehend the origins of intelligence raises intriguing questions about the evolution of learning abilities in natural systems. Why do living organisms possess an inherent drive to acquire knowledge of the unknown? Is this…

Neurons and Cognition · Quantitative Biology 2023-10-05 Alex Ushveridze

Mechanistic models can provide an intuitive and interpretable explanation of network growth by specifying a set of generative rules. These rules can be defined by domain knowledge about real-world mechanisms governing network growth or may…

Social and Information Networks · Computer Science 2025-12-04 Maxwell H Wang , Till Hoffmann , Jukka-Pekka Onnela

The Free Energy Principle (FEP) states that under suitable conditions of weak coupling, random dynamical systems with sufficient degrees of freedom will behave so as to minimize an upper bound, formalized as a variational free energy, on…

Quantum Physics · Physics 2022-07-21 Chris Fields , Karl Friston , James F. Glazebrook , Michael Levin

The ideas of thermodynamics have proved fruitful in the setting of quantum information theory, in particular the notion that when the allowed transformations of a system are restricted, certain states of the system become useful resources…

This paper investigates the competition of two species in a heterogeneous environment subject to the effect of harvesting. The most realistic harvesting case is connected with the intrinsic growth rate, and the harvesting functions are…

Time evolution of number of species (genera, families, and others), population of them, and size distribution of present ones and life times are studied in terms of a new model, where population of each genetic taxon increases by a (random)…

Populations and Evolution · Quantitative Biology 2007-05-23 Caglar Tuncay

A simplified model for the growth of a population is studied in which random effects arise because reproducing individuals have a certain probability of surviving until the next breeding season and hence contributing to the next generation.…

Populations and Evolution · Quantitative Biology 2016-04-05 Henry C. Tuckwell

In a co-evolutionary context, the survive probability of individual elements of a system depends on their relation with their neighbors. The natural selection process depends on the whole population, which is determined by local events…

Biological Physics · Physics 2009-11-13 Juan G. Diaz Ochoa

Biological sequences do not come at random. Instead, they appear with particular frequencies that reflect properties of the associated system or phenomenon. Knowing how biological sequences are distributed in sequence space is thus a…

Biological Physics · Physics 2024-04-18 Wei-Chia Chen , Juannan Zhou , David M. McCandlish

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 general mathematical theory of the necessary…

Artificial Intelligence · Computer Science 2021-08-31 Beren Millidge