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Here we focus on the description of the mechanisms behind the process of information aggregation and decision making, a basic step to understand emergent phenomena in society, such as trends, information spreading or the wisdom of crowds.…

Physics and Society · Physics 2015-04-15 Víctor M. Eguíluz , N. Masuda , J. Fernández-Gracia

In strategic classification, agents modify their features, at a cost, to ideally obtain a positive classification from the learner's classifier. The typical response of the learner is to carefully modify their classifier to be robust to…

Machine Learning · Computer Science 2024-02-15 Lee Cohen , Saeed Sharifi-Malvajerdi , Kevin Stangl , Ali Vakilian , Juba Ziani

A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that agents may hold about the world and the rich language we…

Computation and Language · Computer Science 2025-05-27 Lance Ying , Almog Hillel , Ryan Truong , Vikash K. Mansinghka , Joshua B. Tenenbaum , Tan Zhi-Xuan

We analyze boundedly rational updating from aggregate statistics in a model with binary actions and binary states. Agents each take an irreversible action in sequence after observing the unordered set of previous actions. Each agent first…

Machine Learning · Computer Science 2021-01-11 Itai Arieli , Yakov Babichenko , Manuel Mueller-Frank

Toward explaining the persistence of biased inferences, we propose a framework to evaluate competing (mis)specifications in strategic settings. Agents with heterogeneous (mis)specifications coexist and draw Bayesian inferences about their…

Theoretical Economics · Economics 2023-02-14 Kevin He , Jonathan Libgober

Despite the obvious advantage of simple life forms capable of fast replication, different levels of cognitive complexity have been achieved by living systems in terms of their potential to cope with environmental uncertainty. Against the…

Populations and Evolution · Quantitative Biology 2017-10-18 Luís F Seoane , Ricard Solé

We study a model of consensus decision making, in which a finite group of Bayesian agents has to choose between one of two courses of action. Each member of the group has a private and independent signal at his or her disposal, giving some…

Statistics Theory · Mathematics 2018-04-24 Elchanan Mossel , Omer Tamuz

Complex adaptive systems have been the subject of much recent attention. It is by now well-established that members (`agents') tend to self-segregate into opposing groups characterized by extreme behavior. However, while different social…

Condensed Matter · Physics 2009-11-07 Shahar Hod , Ehud Nakar

Human communication systems, such as language, evolve culturally; their components undergo reproduction and variation. However, a role for selection in cultural evolutionary dynamics is less clear. Often neutral evolution (also known as…

Social and Information Networks · Computer Science 2014-07-01 Nicolas Fay , Monica Tamariz , T Mark Ellison , Dale Barr

We live in a world brimming with uncertainty, where we constantly have to make a lot of decisions under incomplete information. We are firm believers that our subjective belief cannot be computed by rigorous mathematical formula; instead…

Physics and Society · Physics 2023-02-08 Lizhi Xin , Kevin Xin , Houwen Xin

We show that it can be suboptimal for Bayesian decision-making agents employing social learning to use correct prior probabilities as their initial beliefs. We consider sequential Bayesian binary hypothesis testing where each individual…

Information Theory · Computer Science 2026-03-12 Joong Bum Rhim , Vivek K Goyal

We propose and study an evolutionary minority game (EMG) in which the agents are allowed to choose among three possible options. Unlike the original EMG where the agents either win or lose one unit of wealth, the present model assigns one…

Statistical Mechanics · Physics 2007-05-23 Hong-Jun Quan , P. M. Hui , C. Xu , K. F Yip

In this paper, we study how an agent's belief is affected by her neighbors in a social network. We first introduce a general framework, where every agent has an initial belief on a statement, and updates her belief according to her and her…

Artificial Intelligence · Computer Science 2013-09-04 Yi Zhou

When a prediction algorithm serves a collection of users, disparities in prediction quality are likely to emerge. If users respond to accurate predictions by increasing engagement, inviting friends, or adopting trends, repeated learning…

Machine Learning · Computer Science 2025-11-27 Eden Saig , Nir Rosenfeld

We present a theory which describes a recently introduced model of an evolving, adaptive system in which agents compete to be in the minority. The agents themselves are able to evolve their strategies over time in an attempt to improve…

Condensed Matter · Physics 2009-10-31 T. S. Lo , P. M. Hui , N. F. Johnson

We study a setting where a group of agents, each receiving partially informative private signals, seek to collaboratively learn the true underlying state of the world (from a finite set of hypotheses) that generates their joint observation…

Systems and Control · Electrical Eng. & Systems 2019-07-09 Aritra Mitra , John A. Richards , Shreyas Sundaram

For billions of years, evolution has been the driving force behind the development of life, including humans. Evolution endowed humans with high intelligence, which allowed us to become one of the most successful species on the planet.…

Computers and Society · Computer Science 2023-07-21 Dan Hendrycks

We study the voting game where agents' preferences are endogenously decided by the information they receive, and they can collaborate in a group. We show that strategic voting behaviors have a positive impact on leading to the ``correct''…

Computer Science and Game Theory · Computer Science 2023-05-23 Qishen Han , Grant Schoenebeck , Biaoshuai Tao , Lirong Xia

A network of agents attempt to learn some unknown state of the world drawn by nature from a finite set. Agents observe private signals conditioned on the true state, and form beliefs about the unknown state accordingly. Each agent may face…

Machine Learning · Computer Science 2015-03-13 Shahin Shahrampour , Mohammad Amin Rahimian , Ali Jadbabaie

It has long been hypothesized that operating close to the critical state is beneficial for natural, artificial and their evolutionary systems. We put this hypothesis to test in a system of evolving foraging agents controlled by neural…

Neural and Evolutionary Computing · Computer Science 2023-11-28 Sina Khajehabdollahi , Jan Prosi , Emmanouil Giannakakis , Georg Martius , Anna Levina