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In computational social choice, the distortion of a voting rule quantifies the degree to which the rule overcomes limited preference information to select a socially desirable outcome. This concept has been investigated extensively, but…

Computer Science and Game Theory · Computer Science 2023-12-11 Yannai A. Gonczarowski , Gregory Kehne , Ariel D. Procaccia , Ben Schiffer , Shirley Zhang

Both deterministic and indeterministic physical laws are incompatible with control by genuine (non-illusory) free will. We propose that an indeterministic dynamics can be $weakly$ compatible with free will (FW), whereby the latter acts by…

Quantum Physics · Physics 2010-11-23 Chetan S. Mandayam Nayakar , R. Srikanth

Creativity is thought to involve searching and selecting amongst multiple discrete idea candidates. Honing theory predicts that it involves actualizing the potentiality of as few as a single ill-defined idea by viewing it from different…

Neurons and Cognition · Quantitative Biology 2014-09-01 Nicole Carbert , Liane Gabora , Jasmine Schwartz , Apara Ranjan

Learning algorithms are being increasingly adopted in various applications. However, further expansion will require methods that work more automatically. To enable this level of automation, a more powerful solution representation is needed.…

Neural and Evolutionary Computing · Computer Science 2019-02-19 Danilo Vasconcellos Vargas , Junichi Murata

Why do biological and artificial neurons sometimes modularise, each encoding a single meaningful variable, and sometimes entangle their representation of many variables? In this work, we develop a theory of when biologically inspired…

Neurons and Cognition · Quantitative Biology 2025-08-05 Will Dorrell , Kyle Hsu , Luke Hollingsworth , Jin Hwa Lee , Jiajun Wu , Chelsea Finn , Peter E Latham , Tim EJ Behrens , James CR Whittington

In this work we model the dynamics of a population that evolves as a continuous time branching process with a trait structure and ecological interactions in form of mutations and competition between individuals. We generalize existing…

Probability · Mathematics 2020-10-19 Gabriel Berzunza , Anja Sturm , Anita Winter

Most research on adaptive decision-making takes a strategy-first approach, proposing a method of solving a problem and then examining whether it can be implemented in the brain and in what environments it succeeds. We present a method for…

Neural and Evolutionary Computing · Computer Science 2015-09-21 Peter Kvam , Joseph Cesario , Jory Schossau , Heather Eisthen , Arend Hintze

Large language models can exhibit unexpected behavior in the blink of an eye. In a recent computer use demo, a language model switched from coding to Googling pictures of Yellowstone, and these sudden shifts in behavior have also been…

Machine Learning · Computer Science 2025-06-06 Marvin Li , Aayush Karan , Sitan Chen

If the parameters defining the physics of our universe departed from their present values, the observed rich structure and complexity would not be supported. This article considers whether similar fine-tuning of parameters applies to…

Popular Physics · Physics 2020-08-26 Jeffrey M. Shainline

Vision is widely understood as an inference problem. However, two contrasting conceptions of the inference process have each been influential in research on biological vision as well as the engineering of machine vision. The first…

Evolution by Natural Selection is a process by which progeny inherit some properties from their progenitors with small variation. These properties are subject to Natural Selection and are called adaptive traits and carriers of the latter…

Analysis of PDEs · Mathematics 2024-01-29 Gonzalo Galiano , Yosef Cohen

Taking inspiration from biological evolution, we explore the idea of "Can deep neural networks evolve naturally over successive generations into highly efficient deep neural networks?" by introducing the notion of synthesizing new highly…

Computer Vision and Pattern Recognition · Computer Science 2017-02-08 Mohammad Javad Shafiee , Akshaya Mishra , Alexander Wong

Consider a branching process with a homogeneous reproduction law. Sampling a single cell uniformly from the population at a time $T > 0$ and looking along the sampled cell's ancestral lineage, we find that the reproduction law is…

Populations and Evolution · Quantitative Biology 2022-05-30 David Cheek , Samuel G. G. Johnston

Through in-depth thinking and reasoning about the conditions required for cells to maintain unchanged material distribution, it is concluded that life metabolic reactions require high information content. However, the self-replication of a…

Biological Physics · Physics 2024-08-27 Cheng Bi

Aging is a universal consequence of life, yet researchers have identified no universal theme. This manuscript considers aging from the perspective of entropy, wherein things fall apart. We first examine biological information change as a…

Populations and Evolution · Quantitative Biology 2026-04-13 Stephan Baehr , Hans Baehr

Variation and selection are the core principles of Darwinian evolution, yet quantitatively relating the diversity of a population to its capacity to respond to selection is challenging. Here, we examine this problem at a molecular level in…

Populations and Evolution · Quantitative Biology 2016-04-27 Sébastien Boyer , Dipanwita Biswas , Ananda Kumar Soshee , Natale Scaramozzino , Clément Nizak , Olivier Rivoire

Variational autoencoders have been widely applied for natural language generation, however, there are two long-standing problems: information under-representation and posterior collapse. The former arises from the fact that only the last…

Machine Learning · Computer Science 2021-06-17 Xianghong Fang , Haoli Bai , Zenglin Xu , Michael Lyu , Irwin King

The functioning of animal as well as human societies fundamentally relies on cooperation. Yet, defection is often favorable for the selfish individual, and social dilemmas arise. Selection by individuals' fitness, usually the basic driving…

Populations and Evolution · Quantitative Biology 2009-09-26 Jonas Cremer , Tobias Reichenbach , Erwin Frey

A simple model of self-organised learning with no classical (Hebbian) reinforcement is presented. Synaptic connections involved in mistakes are depressed. The model operates at a highly adaptive, probably critical, state reached by extremal…

adap-org · Physics 2008-02-03 Dante R. Chialvo , Per Bak

In the last years the debate on complexity has been developing and developing in transdisciplinary way to meet the need of explanation for highly organized collective behaviors and sophisticated hierarchical arrangements in physical,…

General Physics · Physics 2010-04-26 Ignazio Licata