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Although living organisms are affected by many interrelated and unidentified variables, this complexity does not automatically impose a fundamental limitation on statistical inference. Nor need one invoke such complexity as an explanation…

Data Analysis, Statistics and Probability · Physics 2013-02-06 Drew M. Thomas

This paper presents an experimental study to investigate the learning and decision making behavior of individuals in a human society. Social learning is used as the mathematical basis for modelling interaction of individuals that aim to…

Social and Information Networks · Computer Science 2014-08-25 Maziyar Hamdi , Grayden Solman , Alan Kingstone , Vikram Krishnamurthy

We consider a social system of interacting heterogeneous agents with learning abilities, a model close to Random Field Ising Models, where the random field corresponds to the idiosyncratic willingness to pay. Given a fixed price, agents…

Physics and Society · Physics 2009-11-13 Viktoriya Semeshenko , Mirta B. Gordon , Jean-Pierre Nadal

Respect for persons is a cornerstone value for any conception of research ethics--though how to best realize respect in practice is an ongoing question. In the late 19th and early 20th centuries, "informed consent" emerged as a particular…

Computers and Society · Computer Science 2016-09-13 Elaine Sedenberg , Anna Lauren Hoffmann

Easier access to the internet and social media has made disseminating information through online sources very easy. Sources like Facebook, Twitter, online news sites and personal blogs of self-proclaimed journalists have become significant…

Computation and Language · Computer Science 2021-09-28 Shaily Bhatt , Sakshi Kalra , Naman Goenka , Yashvardhan Sharma

We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively, and independently…

Physics and Society · Physics 2015-05-13 Anne-Ly Do , Lars Rudolf , Thilo Gross

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is…

Social and Information Networks · Computer Science 2018-07-23 Marco Cremonini , Francesca Casamassima

In many settings, an effective way of evaluating objects of interest is to collect evaluations from dispersed individuals and to aggregate these evaluations together. Some examples are categorizing online content and evaluating student…

Computer Science and Game Theory · Computer Science 2016-06-23 Alice Gao , James R. Wright , Kevin Leyton-Brown

The problem of knowing who knows what is multi-faceted. Knowledge and expertise lie on a spectrum and one's expertise in one topic area may have little bearing on one's knowledge in a disparate topic area. In addition, we continue to learn…

Social and Information Networks · Computer Science 2012-04-17 Terrell G. Russell

Automatic narration of events and entities is the need of the hour, especially when live reporting is critical and volume of information to be narrated is huge. This paper discusses the challenges in this context, along with the algorithms…

Artificial Intelligence · Computer Science 2015-10-16 Paramjot Kaur Sarao , Puneet Mittal , Rupinder Kaur

Agents receive private signals about an unknown state. The resulting joint belief distributions are complex and lack a simple characterization. Our key insight is that, when conditioned on the state, the structure of belief distributions…

Theoretical Economics · Economics 2024-11-19 Itai Arieli , Yakov Babichenko , Fedor Sandomirskiy

We study a canonical collective action game with incomplete information. Individuals attempt to coordinate to achieve a shared goal, while also facing a temptation to free-ride. Consuming more similar information about the fundamentals can…

General Economics · Economics 2026-04-10 Deepal Basak , Joyee Deb , Aditya Kuvalekar

When deployed, AI agents will encounter problems that are beyond their autonomous problem-solving capabilities. Leveraging human assistance can help agents overcome their inherent limitations and robustly cope with unfamiliar situations. We…

Machine Learning · Computer Science 2022-06-24 Khanh Nguyen , Yonatan Bisk , Hal Daumé

We study opinion dynamics in a population of interacting adaptive agents voting on a set of complex multidimensional issues. We consider agents which can classify issues into for or against. The agents arrive at the opinions about each…

Physics and Society · Physics 2009-03-11 Renato Vicente , Andre C. R. Martins , Nestor Caticha

We advocate the development of a discipline of interacting with and extracting information from models, both mathematical (e.g. game-theoretic ones) and computational (e.g. agent-based models). We outline some directions for the development…

Multiagent Systems · Computer Science 2021-02-24 Gabriel Istrate

In this technical note, we investigate information quantities of state-dependent communication channels with corrupted information fed back from the receiver. We derive an information identity which can be interpreted as a law of…

Information Theory · Computer Science 2014-02-06 Nicolas Limal

In the wake of the on-going digital revolution, we will see a dramatic transformation of our economy and most of our societal institutions. While the benefits of this transformation can be massive, there are also tremendous risks to our…

Computers and Society · Computer Science 2015-04-16 Dirk Helbing

Throughout history, everyday people have contributed to science through a myriad of volunteer activities. This early participation required training and often involved mentorship from scientists or senior citizen scientists (or, as they…

Computers and Society · Computer Science 2019-07-31 Alison Reiheld , Pamela L. Gay

Sample efficiency is a crucial property of language models with practical implications for training efficiency. In real-world text, information follows a long-tailed distribution. Yet, we expect models to learn and recall frequent and…

Computation and Language · Computer Science 2025-06-23 Daniel Christoph , Max Ploner , Patrick Haller , Alan Akbik

The aim of this paper is to investigate the interplay between knowledge shared by a group of agents and its coalition ability. We investigate this relation in the standard context of imperfect information concurrent game. We assume that…

Artificial Intelligence · Computer Science 2016-11-28 Guifei Jiang , Dongmo Zhang , Laurent Perrussel