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We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples of such decisions are ubiquitous, from robot planning algorithms that rely on pedestrian…

In order to safely operate around humans, robots can employ predictive models of human motion. Unfortunately, these models cannot capture the full complexity of human behavior and necessarily introduce simplifying assumptions. As a result,…

Hierarchical model fitting has become commonplace for case-control studies of cognition and behaviour in mental health. However, these techniques require us to formalise assumptions about the data-generating process at the group level,…

Computers and Society · Computer Science 2020-11-04 Vincent Valton , Toby Wise , Oliver J. Robinson

Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical…

Physics and Society · Physics 2014-11-18 A. E. Allahverdyan , Aram Galstyan

Many biological, psychological and economic experiments have been designed where an organism or individual must choose between two options that have the same expected reward but differ in the variance of reward received. In this way,…

Quantitative Methods · Quantitative Biology 2018-09-20 Jared M. Field , Michael B. Bonsall

Much research has studied foundations for correct and reliable communication-centric systems. A salient approach to correctness uses session types to enforce structured communications; a recent approach to reliability uses reversible…

Logic in Computer Science · Computer Science 2016-06-21 Claudio A. Mezzina , Jorge A. Pérez

Robots today often miss a key ingredient of truly intelligent behavior: the ability to reflect on their own cognitive processes and decisions. In humans, this self-monitoring or metacognition is crucial for learning, decision making and…

The emergent dynamics of complex systems often arise from the internal dynamical interactions among different elements and hence is to be modeled using multiple variables that represent the different dynamical processes. When such systems…

Chaotic Dynamics · Physics 2024-11-05 Shivam Kumar , R. Misra , G. Ambika

An important use of machine learning is to learn what people value. What posts or photos should a user be shown? Which jobs or activities would a person find rewarding? In each case, observations of people's past choices can inform our…

Artificial Intelligence · Computer Science 2015-12-21 Owain Evans , Andreas Stuhlmueller , Noah D. Goodman

This paper introduces a new behavioral system model with distinct external and internal signals possibly evolving on different time scales. This allows to capture abstraction processes or signal aggregation in the context of control and…

Systems and Control · Computer Science 2014-02-17 Anne-Kathrin Schmuck , Jörg Raisch

This paper studies the problem of recursively estimating the weighted adjacency matrix of a network out of a temporal sequence of binary-valued observations. The observation sequence is generated from nonlinear networked dynamics in which…

Systems and Control · Electrical Eng. & Systems 2019-12-06 Yu Xing , Xingkang He , Haitao Fang , Karl Henrik Johansson

As models of cognition grow in complexity and number of parameters, Bayesian inference with standard methods can become intractable, especially when the data-generating model is of unknown analytic form. Recent advances in simulation-based…

Machine Learning · Statistics 2020-07-14 Stefan T. Radev , Andreas Voss , Eva Marie Wieschen , Paul-Christian Bürkner

The pairwise maximum entropy model, also known as the Ising model, has been widely used to analyze the collective activity of neurons. However, controversy persists in the literature about seemingly inconsistent findings, whose significance…

Disordered Systems and Neural Networks · Physics 2019-03-13 Cristian Zanoci , Nima Dehghani , Max Tegmark

Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single,…

Neurons and Cognition · Quantitative Biology 2023-01-11 Jing Shuang Li , Anish A. Sarma , Terrence J. Sejnowski , John C. Doyle

Biological systems perform complex multi-step processes in a reproducible way despite underlying stochasticity. The standard explanation is micromanagement by molecular machinery that recognizes and corrects specific errors. Here we study…

Populations and Evolution · Quantitative Biology 2026-05-14 Riccardo Ravasio , Kabir Husain , Constantine G. Evans , Rob Phillips , Marco Ribezzi-Crivellari , Jack W. Szostak , Arvind Murugan

In social systems, meaning can be communicated in addition to underlying processes of the information exchange. Meaning processing incurs on information processing with hindsight, while information processing recursively follows the time…

Physics and Society · Physics 2009-12-08 Loet Leydesdorff , Daniel M. Dubois

We propose a simple model to explore an educational phenomenon where the correct answer emerges from group discussion. We construct our model based on several plausible assumptions: (i) We tend to follow peers' opinions. However, if a…

Physics and Society · Physics 2025-05-27 Jibeom Seo , Beom Jun Kim

Time perception - how humans and animals perceive the passage of time - forms the basis for important cognitive skills such as decision-making, planning, and communication. In this work, we propose a framework for examining the mechanisms…

Systems and Control · Electrical Eng. & Systems 2023-11-08 Inês Lourenço , Robert Mattila , Rodrigo Ventura , Bo Wahlberg

Much research has been conducted on how consumption is related to human relations, for example, consumer communities organized around specific brands, or the way people use products to define their own identity and transmit a desired image.…

Social and Information Networks · Computer Science 2024-01-10 Lizardo Vargas-Bianchi

Developing and fielding complex systems requires proof that they are reliably correct with respect to their design and operating requirements. Especially for autonomous systems which exhibit unanticipated emergent behavior, fully…

Software Engineering · Computer Science 2024-02-28 Matthew Litton , Doron Drusinsky , James Bret Michael
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