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In the last few decades or so, we witness a paradigm shift in our nature studies - from a data-processing based computational approach to an information-processing based cognitive approach. The process is restricted and often misguided by…

Computational Engineering, Finance, and Science · Computer Science 2015-05-20 Emanuel Diamant

Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that…

Computational Physics · Physics 2025-04-04 Tomáš Vantuch , Ivan Zelinka , Andrew Adamatzky , Norbert Marwan

Living organisms rely on molecular networks, such as gene circuits and signaling pathways, for information processing and robust decision-making in crowded, noisy environments. Recent advances show that interacting biomolecules…

In this Chapter, we ask questions (1) What is the right way to measure the quality of information processing in a biological system? and (2) What can real-life organisms do in order to improve their performance in information-processing…

Quantitative Methods · Quantitative Biology 2010-11-25 Ilya Nemenman

Concomitant with the evolution of biological diversity must have been the evolution of mechanisms that facilitate evolution, due to the essentially infinite complexity of protein sequence space. We describe how evolvability can be an object…

Populations and Evolution · Quantitative Biology 2009-11-10 David J. Earl , Michael W. Deem

Living systems operate far from equilibrium, yet few general frameworks provide global bounds on biological transients. In high-dimensional biological networks like ecosystems, long transients arise from the separate timescales of…

Biological Physics · Physics 2025-04-15 William Gilpin

The field of artificial intelligence faces significant challenges in achieving both biological plausibility and computational efficiency, particularly in visual learning tasks. Current artificial neural networks, such as convolutional…

Machine Learning · Computer Science 2024-09-27 Jacobo Ruiz , Manas Gupta

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

The ideas of optimization of learning algorithms in Artificial Neural Networks are reviewed emphasizing generic properties and the online implementations are interpreted from a biological perspective. A simple model of the relevant…

Disordered Systems and Neural Networks · Physics 2017-02-08 N. Caticha , O. Kinouchi

In real-world systems, phase transitions often materialize abruptly, making it difficult to design appropriate controls that help uncover underlying processes. Some agent-based computational models display transformations similar to phase…

Physics and Society · Physics 2018-10-10 S. S. Chanda , B. McKelvey

Humans' distinctive role in the world can largely be attributed to our capacity for iterated learning, a process by which knowledge is expanded and refined over generations. A range of theories seek to explain why humans are so adept at…

Social and Information Networks · Computer Science 2025-12-02 Ben Prystawski , Dilip Arumugam , Noah D. Goodman

Early theories of perception as probabilistic inference propose that uncertainty about the interpretation of sensory input is represented as a probability distribution over many interpretations -- a relatively complex representation.…

Neurons and Cognition · Quantitative Biology 2025-10-01 Andrew Jun Lee , Daniel Turek , Omer Daglar Tanrikulu

The study of the fundamental limits of information systems is a central theme in information theory. Both the traditional analytical approach and the recently proposed computational approach have significant limitations, where the former is…

Information Theory · Computer Science 2022-05-04 Wenjing Chen , Chao Tian

The long-term growth rate of populations in varying environments quantifies the evolutionary value of processing the information that biological individuals inherit from their ancestors and acquire from their environment. Previous models…

Populations and Evolution · Quantitative Biology 2021-06-30 Anton S Zadorin , Olivier Rivoire

Environmental fluctuations can shape replicator dynamics, with important consequences for both prebiotic and modern ecosystems. However, it remains unclear how simple replicators can acquire and use information about fluctuating…

Biological Physics · Physics 2026-05-25 Jordi Piñero , Damian R. Sowinski , Gourab Ghoshal , Adam Frank , Artemy Kolchinsky

Central to the functioning of a living cell is its ability to control the readout or expression of information encoded in the genome. In many cases, a single transcription factor protein activates or represses the expression of many genes.…

Molecular Networks · Quantitative Biology 2013-05-29 Aleksandra M. Walczak , Gapser Tkacik , William Bialek

We explain how hierarchical organization of biological systems emerges naturally during evolution, through a transition in the units of individuality. We will show how these transitions are the result of competing selective forces operating…

Populations and Evolution · Quantitative Biology 2015-06-16 Cameron Smith , Matthieu Laneuville , Nicholas Guttenberg

Living organisms are not just random collections of organic molecules. There is continuous information processing going on in the apparent bouncing around of molecules of life. Optimisation criteria in this information processing can be…

Quantum Physics · Physics 2007-05-23 Apoorva Patel

Many biological regulatory systems process signals out of steady state and respond with a physiological delay. A simple model of regulation which respects these features shows how the ability of a delayed output to transmit information is…

Molecular Networks · Quantitative Biology 2013-08-13 Francesca Mancini , Chris H. Wiggins , Matteo Marsili , Aleksandra M. Walczak

This paper presents the thesis that all learning agents of finite information size are limited by their informational structure in what goals they can efficiently learn to achieve in a complex environment. Evolutionary change is critical…

Artificial Intelligence · Computer Science 2013-04-03 Alok Raj