activity
20182026
most citedLearning to Correlate in Multi-Player General-Sum Sequential Games

20 citations · 69 across the 50 of their papers we have counts for

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Showing 2022Show all

9 papers · 1 filter

cs.LG2022

A Unifying Framework for Online Optimization with Long-Term Constraints

Matteo Castiglioni, Andrea Celli, Alberto Marchesi +2

We study online learning problems in which a decision maker has to take a sequence of decisions subject to long-term constraints. The goal of the decision maker is to maximize…

cs.LG2022★ 3 cited

Sequential Information Design: Learning to Persuade in the Dark

Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi +2

We study a repeated information design problem faced by an informed sender who tries to influence the behavior of a self-interested receiver. We consider settings where the receive…

cs.GT2022

Last-iterate Convergence to Trembling-hand Perfect Equilibria

Martino Bernasconi, Alberto Marchesi, Francesco Trovò

Designing efficient algorithms to find Nash equilibrium (NE) refinements in sequential games is of paramount importance in practice. Indeed, it is well known that the NE has severa…

cs.GT2022★ 2 cited

The Power of Media Agencies in Ad Auctions: Improving Utility through Coordinated Bidding

Giulia Romano, Matteo Castiglioni, Alberto Marchesi +1

The increasing competition in digital advertising induced a proliferation of media agencies playing the role of intermediaries between advertisers and platforms selling ad slots. W…

cs.GT2022★ 1 cited

Designing Menus of Contracts Efficiently: The Power of Randomization

Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

We study hidden-action principal-agent problems in which a principal commits to an outcome-dependent payment scheme (called contract) so as to incentivize the agent to take a costl…

cs.GT2022★ 2 cited

Bayesian Persuasion Meets Mechanism Design: Going Beyond Intractability with Type Reporting

Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

Bayesian persuasion studies how an informed sender should partially disclose information so as to influence the behavior of self-interested receivers. In the last years, a growing…

cs.GT2022★ 1 cited

Efficiency of Ad Auctions with Price Displaying

Matteo Castiglioni, Diodato Ferraioli, Nicola Gatti +2

Most of the economic reports forecast that almost half of the worldwide market value unlocked by AI over the next decade (up to 6 trillion USD per year) will be in marketing&sales.…

cs.GT2022★ 1 cited

Public Signaling in Bayesian Ad Auctions

Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi +2

We study signaling in Bayesian ad auctions, in which bidders' valuations depend on a random, unknown state of nature. The auction mechanism has complete knowledge of the actual sta…

cs.GT2022

Signaling in Posted Price Auctions

Matteo Castiglioni, Giulia Romano, Alberto Marchesi +1

We study single-item single-unit Bayesian posted price auctions, where buyers arrive sequentially and their valuations for the item being sold depend on a random, unknown state of…