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The purpose of this paper is to abstractly describe the notion of a generative mechanism that implements a code and to provide a number of examples including the DNA-RNA machinery that implements the genetic code, Chomsky's Principles &…

Information Theory · Computer Science 2021-05-11 David Ellerman

To many Chomsky's debates with Quine and Skinner are an updated version of the Rationalist Empiricist debates of the 17th century. The consensus being that Chomsky's Rationalism was victorious. This dispute has reemerged with the advent of…

Computation and Language · Computer Science 2024-10-18 David King

Biological systems are generally complicated and/or complex. In the former approach, one sets up a model with a large number of parameters to describe the system in detail. The latter approach focuses on understanding the universal aspects…

Biological Physics · Physics 2026-03-19 Kunihiko Kaneko

Understanding how the structure of community interactions is modified by coevolution is vital for understanding system responses to change at all scales. However, in absence of a group selection process, collective community behaviours…

Populations and Evolution · Quantitative Biology 2015-06-23 Daniel A. Power , Richard A. Watson , Eörs Szathmáry , Rob Mills , Simon T Powers , C Patrick Doncaster , Błażej Czapp

What does it mean to know language? Since the Chomskian revolution, one popular answer to this question has been: to possess a generative grammar that exclusively licenses certain syntactic structures. Decades later, not even an…

Computation and Language · Computer Science 2023-03-15 Shimon Edelman

The scheme of a unified Darwinian evolutionary theory for physical and biological systems is described. Every physical system is methodologically endowed with a classical information processor what turns every system into an agent being…

General Physics · Physics 2019-11-26 Carlos Baladron , Andrei Khrennikov

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated…

Adaptation and Self-Organizing Systems · Physics 2013-03-18 Hong Qian

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

The theory of interaction-based evolution argues that, at the most basic level of analysis, there is a third alternative for how adaptive evolution works besides a) accidental mutation and natural selection and b) Lamarckism, namely, c)…

Populations and Evolution · Quantitative Biology 2016-05-25 Adi Livnat

A tendency in biological theorizing is to formulate principles above or equal to Evolution by Variation and Selection of Darwin and Wallace. In this letter I analyze one such recent proposal which did so for the developmental ascendency. I…

Populations and Evolution · Quantitative Biology 2007-08-08 P Ao

The evolution of cognition is frequently discussed as the evolution of cognitive abilities or the evolution of some neuronal structures in the brain. However, since such traits or abilities are often highly complex, understanding their…

Neurons and Cognition · Quantitative Biology 2025-06-27 Arnon Lotem , Joseph Y. Halpern

We present a critical assessment of Piantadosi's (2023) claim that "Modern language models refute Chomsky's approach to language," focusing on four main points. First, despite the impressive performance and utility of large language models…

Computation and Language · Computer Science 2023-08-08 Jordan Kodner , Sarah Payne , Jeffrey Heinz

A central biological question is how natural organisms are so evolvable (capable of quickly adapting to new environments). A key driver of evolvability is the widespread modularity of biological networks--their organization as functional,…

Populations and Evolution · Quantitative Biology 2015-03-13 Jeff Clune , Jean-Baptiste Mouret , Hod Lipson

Microbiological systems evolve to fulfill their tasks with maximal efficiency. The immune system is a remarkable example, where self-non self distinction is accomplished by means of molecular interaction between self proteins and antigens,…

Cell Behavior · Quantitative Biology 2013-08-26 Marcio Argollo de Menezes , Edgardo Brigatti , Veit Schwämmle

Biological systems, unlike physical or chemical systems, are characterized by the very inhomogeneous distribution of their components. The immune system, in particular, is notable for self-organizing its structure. Classically, the dynamics…

Statistical Mechanics · Physics 2007-05-23 Yoram Louzoun , Sorin Solomon , Henri Atlan , Irun R. Cohen

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

Many biological networks have to filter out useful information from a vast excess of spurious interactions. We use computational evolution to predict design features of networks processing ligand categorization. The important problem of…

Molecular Networks · Quantitative Biology 2013-05-27 Jean-Benoît Lalanne , Paul François

We study the probabilities of evolution based on random mutations and natural selection. We conclude that evolution to multicellular eukaryots, or even prokaryots, is unlikely to be the result of only random mutations. Complex organisms…

Populations and Evolution · Quantitative Biology 2007-05-23 B. Hoeneisen , G. Trueba

Environmentally-induced superselection or "einselection" has been proposed as an observer-independent mechanism by which apparently classical systems "emerge" from physical interactions between degrees of freedom described completely…

Quantum Physics · Physics 2012-10-23 Chris Fields

Significant advances have been made in artificial systems by using biological systems as a guide. However, there is often little interaction between computational models for emergent communication and biological models of the emergence of…

Machine Learning · Computer Science 2020-01-01 Travis LaCroix
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