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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

In a multi-party machine learning system, different parties cooperate on optimizing towards better models by sharing data in a privacy-preserving way. A major challenge in learning is the incentive issue. For example, if there is…

Multiagent Systems · Computer Science 2020-08-11 Mengjing Chen , Yang Liu , Weiran Shen , Yiheng Shen , Pingzhong Tang , Qiang Yang

We study the problem of repeated two-sided matching with uncertain preferences (two-sided bandits), and no explicit communication between agents. Recent work has developed algorithms that converge to stable matchings when one side (the…

Multiagent Systems · Computer Science 2025-08-13 Gaurab Pokharel , Sanmay Das

We all have preferences when multiple choices are available. If we insist on satisfying our preferences only, we may suffer a loss due to conflicts with other people's identical selections. Such a case applies when the choice cannot be…

Theoretical Economics · Economics 2023-02-21 Hiroaki Shinkawa , Nicolas Chauvet , Guillaume Bachelier , André Röhm , Ryoichi Horisaki , Makoto Naruse

Fairness in clustering has been considered extensively in the past; however, the trade-off between the two objectives -- e.g., can we sacrifice just a little in the quality of the clustering to significantly increase fairness, or…

Machine Learning · Computer Science 2024-08-20 Rashida Hakim , Ana-Andreea Stoica , Christos H. Papadimitriou , Mihalis Yannakakis

The problem of peer prediction is to elicit information from agents in settings without any objective ground truth against which to score reports. Peer prediction mechanisms seek to exploit correlations between signals to align incentives…

Computer Science and Game Theory · Computer Science 2016-06-20 Victor Shnayder , Arpit Agarwal , Rafael Frongillo , David C. Parkes

Classification, recommendation, and ranking problems often involve competing goals with additional constraints (e.g., to satisfy fairness or diversity criteria). Such optimization problems are quite challenging, often involving non-convex…

Machine Learning · Computer Science 2021-02-16 Gurpreet Singh , Soumyajit Gupta , Matthew Lease , Clint Dawson

Optimization problems have been the subject of statistical physics approximations. A specially relevant and general scenario is provided by optimization methods considering tradeoffs between cost and efficiency, where optimal solutions…

Statistical Mechanics · Physics 2015-09-16 Luís F. Seoane , Ricard V. Solé

Extensive monitoring systems generate data that is usually compressed for network transmission. This compressed data might then be processed in the cloud for tasks such as anomaly detection. However, compression can potentially impair the…

Signal Processing · Electrical Eng. & Systems 2025-09-30 Andriy Enttsel , Alex Marchioni , Andrea Zanellini , Mauro Mangia , Gianluca Setti , Riccardo Rovatti

We investigate disagreement and polarization in a social network with two polarizing sources of information. First, we define disagreement and polarization indices in two-party leader-follower models of opinion dynamics. We then give…

Social and Information Networks · Computer Science 2020-05-18 Yuhao Yi , Stacy Patterson

An equilibrium is communication-proof if it is unaffected by new opportunities to communicate and renegotiate. We characterize the set of equilibria of coordination games with pre-play communication in which players have private preferences…

Theoretical Economics · Economics 2023-11-14 Yuval Heller , Christoph Kuzmics

Bilateral bargaining under incomplete information provides a controlled testbed for evaluating large language model (LLM) agent capabilities. Bilateral trade demands individual rationality, strategic surplus maximization, and cooperation to…

Computer Science and Game Theory · Computer Science 2026-04-21 Dirk Bergemann , Soheil Ghili , Xinyang Hu , Chuanhao Li , Zhuoran Yang

The issue of fairness in recommendation is becoming increasingly essential as Recommender Systems touch and influence more and more people in their daily lives. In fairness-aware recommendation, most of the existing algorithmic approaches…

Information Retrieval · Computer Science 2022-01-04 Yingqiang Ge , Xiaoting Zhao , Lucia Yu , Saurabh Paul , Diane Hu , Chu-Cheng Hsieh , Yongfeng Zhang

In many two-sided markets, the parties to be matched have incomplete information about their characteristics. We consider the settings where the parties engaged are extremely patient and are interested in long-term partnerships. Hence, once…

Computer Science and Game Theory · Computer Science 2019-08-30 Kartik Ahuja , Mihaela van der Schaar

We examine receiver-optimal mechanisms for aggregating information divided across many biased senders. Each sender privately observes an unconditionally independent signal about an unknown state, so no sender can verify another's report. A…

Theoretical Economics · Economics 2025-08-05 James Best , Daniel Quigley , Maryam Saeedi , Ali Shourideh

This paper studies a communication game between an uninformed decision maker and two perfectly informed senders with conflicting interests. Senders can misreport information at a cost that increases with the size of the misrepresentation.…

Theoretical Economics · Economics 2023-04-17 Federico Vaccari

In persuasion problems where the receiver's action is one-dimensional and his utility is single-peaked, optimal signals are characterized by duality, based on a first-order approach to the receiver's problem. A signal is optimal iff the…

Theoretical Economics · Economics 2022-08-31 Anton Kolotilin , Roberto Corrao , Alexander Wolitzky

We study individual rational, Pareto optimal, and incentive compatible mechanisms for auctions with heterogeneous items and budget limits. For multi-dimensional valuations we show that there can be no deterministic mechanism with these…

Computer Science and Game Theory · Computer Science 2012-10-01 Paul Duetting , Monika Henzinger , Martin Starnberger

We study an opinion dynamics model in which agents reach compromise via pairwise interactions. When the opinions of two agents are sufficiently close, they both acquire the average of their initial opinions; otherwise, they do not interact.…

Statistical Mechanics · Physics 2009-11-07 E. Ben-Naim , P. L. Krapivsky , S. Redner

We consider a two-asset non-linear model of option pricing in an environment where the correlation is not known precisely, but varies between two known values. First we discuss the non-negativity of the solution of the equation. Next, we…

Numerical Analysis · Mathematics 2015-09-11 Miglena N. Koleva , Lubin G. Vulkov
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