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Related papers: Signaling Design

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Supervised learning typically focuses on learning transferable representations from training examples annotated by humans. While rich annotations (like soft labels) carry more information than sparse annotations (like hard labels), they are…

We model competition on a credence goods market governed by an imperfect label, signaling high quality, as a rank-order tournament between firms. In this market interaction, asymmetric firms jointly and competitively control the aggregate…

Theoretical Economics · Economics 2025-08-28 Daniel Rehsmann , Béatrice Roussillon , Paul Schweinzer

We examine a controlled school choice model where students are categorized into different types, and the distribution of these types within a school influences its priority structure. This study provides a general framework that integrates…

Theoretical Economics · Economics 2025-03-25 Minoru Kitahara , Yasunori Okumura

This paper characterizes informational outcomes in a model of dynamic signaling with vanishing commitment power. It shows that contrary to popular belief, informative equilibria with payoff-relevant signaling can exist without requiring…

Theoretical Economics · Economics 2024-05-17 Egor Starkov

Traditional economic models typically treat private information, or signals, as generated from some underlying state. Recent work has explicated alternative models, where signals correspond to interpretations of available information. We…

Computer Science and Game Theory · Computer Science 2012-02-20 Michael P. Wellman , Lu Hong , Scott E. Page

Most products are produced and sold by supply chain networks, where an interconnected network of producers and intermediaries set prices to maximize their profits. I show that there exists a unique equilibrium in a price-setting game on a…

Computer Science and Game Theory · Computer Science 2019-04-16 Toomas Hinnosaar

In the new digital age, information is available in large quantities. Since information consumes primarily the attention of its recipients, the scarcity of attention is becoming the main limiting factor. In this study, we investigate the…

Social and Information Networks · Computer Science 2014-11-26 Uzay Cetin , Haluk O. Bingol

There is growing experimental evidence that $Q$-learning agents may learn to charge supracompetitive prices. We provide the first theoretical explanation for this behavior in infinite repeated games. Firms update their pricing policies…

General Economics · Economics 2025-05-30 Cristian Chica , Yinglong Guo , Gilad Lerman

We study a novel approach to information design in the standard traffic model of network congestion games. It captures the natural condition that the demand is unknown to the users of the network. A principal (e.g., a mobility service)…

Computer Science and Game Theory · Computer Science 2023-10-13 Svenja M. Griesbach , Martin Hoefer , Max Klimm , Tim Koglin

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

A sender with private preferences would like to influence a receiver's action by providing information through a statistical test. The technology for information production is controlled by a monopolist intermediary, who offers a menu of…

Theoretical Economics · Economics 2025-02-18 Raphael Boleslavsky , Aaron Kolb

A competitive learning model was introduced in Ref. 1 (A. Mehta and J. M. Luck, Phys. Rev. E 60, 5, 1999), in which the learning is outcome-related. Every individual chooses between a pair of existing strategies or types, guided by a…

Adaptation and Self-Organizing Systems · Physics 2011-07-11 Gaurang Mahajan , Anita Mehta

The theory of two-sided matching has been extensively developed and applied to many real-life application domains. As the theory has been applied to increasingly diverse types of environments, researchers and practitioners have encountered…

Computer Science and Game Theory · Computer Science 2024-02-05 Sung-Ho Cho , Kei Kimura , Kiki Liu , Kwei-guu Liu , Zhengjie Liu , Zhaohong Sun , Kentaro Yahiro , Makoto Yokoo

Persistent economic competition is often justified as a mechanism of innovation, efficiency, and welfare maximization. Yet empirical evidence across disciplines reveals that competition systematically generates fragility, inequality, and…

Theoretical Economics · Economics 2025-06-16 Marcelo S. Tedesco , Gonzalo Marquez

Social marketing is becoming increasingly important in contemporary business. Central to social marketing is quantifying how consumers choose between alternatives and how they influence each other. This work considers a new but simple…

Social and Information Networks · Computer Science 2014-05-05 Jeremy Chen

Models of social learning feature either binary signals or abstract signal structures often deprived of micro-foundations. Both models are limited when analyzing interim results or performing empirical analysis. We present a method of…

Theoretical Economics · Economics 2020-02-26 Amir Ban , Moran Koren

We study decentralized markets with the presence of middlemen, modeled by a non-cooperative bargaining game in trading networks. Our goal is to investigate how the network structure of the market and the role of middlemen influence the…

Computer Science and Game Theory · Computer Science 2013-07-09 Thanh Nguyen , Vijay G. Subramanian , Randall A. Berry

This paper studies a Stackelberg game wherein a sender (leader) attempts to shape the information of a less informed receiver (follower) who in turn takes an action that determines the payoff for both players. The sender chooses signals to…

Computer Science and Game Theory · Computer Science 2022-10-07 Reema Deori , Ankur A. Kulkarni

We argue that deterministic market clearing formulations introduce arbitrary distortions between day-ahead and expected real-time prices that bias economic incentives and block diversification. We extend and analyze the stochastic clearing…

Economics · Quantitative Finance 2015-11-27 Victor M. Zavala , Kibaek Kim , Mihai Anitescu , John Birge

Active learning is a learning strategy whereby the machine learning algorithm actively identifies and labels data points to optimize its learning. This strategy is particularly effective in domains where an abundance of unlabeled data…

Machine Learning · Computer Science 2024-03-05 Zan-Kai Chong , Hiroyuki Ohsaki , Bryan Ng