1 citations · 1 across the 13 of their papers we have counts for
16 papers
Marrying Pricing and Advertising with LLMs
Alessandro Barro, Francesco Bacchiocchi, Francesco Emanuele Stradi +1
We study a sequential pricing problem in which a seller jointly posts a price and an advertisement generated by a large language model (LLM). The seller aims to maximize revenue un…
Support-Dependent Regret Rates for Profit Maximization in Multilateral Trade
Francesco Bacchiocchi, Matteo Castiglioni, Anna Lunghi +1
We study online profit maximization in multilateral trade, a setting that generalizes both dynamic pricing and bilateral trade. At each round, an intermediary posts prices to buyer…
An Efficient Minimax-Optimal Algorithm for Adversarial -Set Bandits
Francesco Bacchiocchi, Tommaso Cesari, Roberto Colomboni
We study adversarial combinatorial bandits with -set actions, where at each round the learner selects out of items and observes only the aggregate loss of the selected i…
No Extra Signals Needed: The Uniform Price of Explainable Information Design
Francesco Bacchiocchi, Tommaso Cesari, Roberto Colomboni
In information design, an informed sender aims to influence a receiver's decision by committing to a signaling scheme. However, optimal signaling schemes often rely on randomizatio…
Multi-Armed Bandits With Best-Action Queries
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi +1
We study \emph{multi-armed bandits} (MABs) augmented with \emph{best-action queries}, in which the learner may additionally query an oracle that reveals the best arm in the current…
Learning in Bayesian Stackelberg Games With Unknown Follower's Types
Matteo Bollini, Francesco Bacchiocchi, Samuel Coutts +2
We study online learning in Bayesian Stackelberg games, where a leader repeatedly interacts with a follower whose unknown private type is independently drawn at each round from an…
Regret Minimization for Piecewise Linear Rewards: Contracts, Auctions, and Beyond
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi +1
Most microeconomic models of interest involve optimizing a piecewise linear function. These include contract design in hidden-action principal-agent problems, selling an item in po…
Contract Design Under Approximate Best Responses
Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni +2
Principal-agent problems model scenarios where a principal incentivizes an agent to take costly, unobservable actions through the provision of payments. Such problems are ubiquitou…
Online Bayesian Persuasion Without a Clue
Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni +2
We study online Bayesian persuasion problems in which an informed sender repeatedly faces a receiver with the goal of influencing their behavior through the provision of payoff-rel…
Contracting With a Reinforcement Learning Agent by Playing Trick or Treat
Matteo Bollini, Francesco Bacchiocchi, Matteo Castiglioni +2
We study principal-agent problems where a farsighted agent takes costly actions in an MDP. The core challenge in these settings is that agent's actions are hidden to the principal,…
The Sample Complexity of Stackelberg Games
Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni +2
Stackelberg games (SGs) constitute the most fundamental and acclaimed models of strategic interactions involving some form of commitment. Moreover, they form the basis of more elab…
Markov Persuasion Processes: Learning to Persuade from Scratch
Francesco Bacchiocchi, Francesco Emanuele Stradi, Matteo Castiglioni +2
In Bayesian persuasion, an informed sender strategically discloses information to a receiver so as to persuade them to undertake desirable actions. Recently, a growing attention ha…
Learning Optimal Contracts: How to Exploit Small Action Spaces
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi +1
We study principal-agent problems in which a principal commits to an outcome-dependent payment scheme -- called contract -- in order to induce an agent to take a costly, unobservab…
Selling Information while Being an Interested Party
Matteo Castiglioni, Francesco Bacchiocchi, Alberto Marchesi +2
We study the algorithmic problem faced by an information holder (seller) who wants to optimally sell such information to a budged-constrained decision maker (buyer) that has to und…
Autoregressive Bandits
Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran +4
Autoregressive processes naturally arise in a large variety of real-world scenarios, including stock markets, sales forecasting, weather prediction, advertising, and pricing. When…
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…