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The information flow inside a P2P network is highly dependent on the network structure. In order to ease the diffusion of relevant data toward interested peers, many P2P protocols gather similar nodes by putting them in direct contact. With…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-19 Ranieri Baraglia , Patrizio Dazzi , Matteo Mordacchini , Laura Ricci , Luca Alessi

Most companies' new business practices are based on customer data. These practices have raised privacy concerns because of the associated risks. Privacy laws require companies to gain customer consent before using their information, which…

Computers and Society · Computer Science 2016-06-06 Christian Fernando Libaque-Saenz , Younghoon Chang , Siew Fan Wong , Hwansoo Lee

This chapter examines the link between delegation and lobbying, two themes central to political economy. Delegation models explore how legislatures manage uncertainty and control bureaucratic agents, while lobbying models analyze how…

Theoretical Economics · Economics 2025-11-24 Thomas Groll , Sharyn O'Halloran

Opponent modeling consists in modeling the strategy or preferences of an agent thanks to the data it provides. In the context of automated negotiation and with machine learning, it can result in an advantage so overwhelming that it may…

Artificial Intelligence · Computer Science 2017-01-02 Cédric Buron , Sylvain Ductor , Zahia Guessoum

Slanted news coverage strongly affects public opinion. This is especially true for coverage on politics and related issues, where studies have shown that bias in the news may influence elections and other collective decisions. Due to its…

Computers and Society · Computer Science 2021-10-19 Felix Hamborg , Timo Spinde , Kim Heinser , Karsten Donnay , Bela Gipp

We study an information theoretic privacy mechanism design problem for two scenarios where the private data is either observable or hidden. In each scenario, we first consider bounded mutual information as privacy leakage criterion, then we…

Information Theory · Computer Science 2022-12-26 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

Human-robot interaction exerts influence towards the human, which often changes behavior. This article explores an externality of this changed behavior - preference change. It expands on previous work on preference change in AI systems.…

Robotics · Computer Science 2022-06-22 Matija Franklin , Hal Ashton

Academic research in recommender systems has been greatly focusing on the accuracy-related measures of recommendations. Even when non-accuracy measures such as popularity bias, diversity, and novelty are studied, it is often solely from the…

Information Retrieval · Computer Science 2020-07-03 Himan Abdollahpouri , Masoud Mansoury

This paper presents a new rationale for a self-interested economic elite voluntarily extending property rights. When agents make endogenous investment decisions, there is a commitment problem. Ex-post, the elite face strong incentives to…

Theoretical Economics · Economics 2024-09-02 Alastair Langtry

Transparency of information disclosure has always been considered an instrumental component of effective governance, accountability, and ethical behavior in any organization or system. However, a natural question follows: \emph{what is the…

Computer Science and Game Theory · Computer Science 2023-12-01 Tao Li , Quanyan Zhu

We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous work on Bayesian inverse reinforcement learning and allows us…

Machine Learning · Statistics 2011-06-30 Constantin Rothkopf , Christos Dimitrakakis

I study a social learning model in which the object to learn is a strategic player's endogenous actions rather than an exogenous state. A patient seller faces a sequence of buyers and decides whether to build a reputation for supplying high…

Theoretical Economics · Economics 2020-11-03 Harry Pei

Despite strong evidence for peer effects, little is known about how individuals balance intrinsic preferences and social learning in different choice environments. Using a combination of experiments and discrete choice modeling, we show…

General Economics · Economics 2024-02-29 Fabian Dvorak , Urs Fischbacher

AI systems have been known to amplify biases in real-world data. Explanations may help human-AI teams address these biases for fairer decision-making. Typically, explanations focus on salient input features. If a model is biased against…

Artificial Intelligence · Computer Science 2024-04-10 Navita Goyal , Connor Baumler , Tin Nguyen , Hal Daumé

It is shown that in the case of a single decision maker who optimizes several possibly conflicting objectives, the amount of information available in preference relations among pairs of possible decisions, when compared with all other…

Optimization and Control · Mathematics 2007-05-23 Elemer E Rosinger

People are often reluctant to incorporate information produced by algorithms into their decisions, a phenomenon called ``algorithm aversion''. This paper shows how algorithm aversion arises when the choice to follow an algorithm conveys…

Theoretical Economics · Economics 2024-08-02 Gregory Weitzner

How do incentive levels affect strategic behaviour? We address this with an experiment that separately identifies own- and opponent-incentive effects in two dominance-solvable games that differ in strategic complexity. Higher own incentives…

Theoretical Economics · Economics 2026-03-30 Teresa Esteban-Casanelles , Duarte Gonçalves

There has been considerable work on reasoning about the strategic ability of agents under imperfect information. However, existing logics such as Probabilistic Strategy Logic are unable to express properties relating to information…

Artificial Intelligence · Computer Science 2025-01-07 Chunyan Mu , Nima Motamed , Natasha Alechina , Brian Logan

Information disclosure can compromise privacy when revealed information is correlated with private information. We consider the notion of inferential privacy, which measures privacy leakage by bounding the inferential power a Bayesian…

Cryptography and Security · Computer Science 2024-12-16 Shuaiqi Wang , Shuran Zheng , Zinan Lin , Giulia Fanti , Zhiwei Steven Wu

We need to rethink our approach to defend privacy on the internet. Currently, policymakers focus heavily on the idea of informed consent as a means to defend privacy. For instance, in many countries the law requires firms to obtain an…

Computers and Society · Computer Science 2025-12-08 Frederik Zuiderveen Borgesius