Search Results for author: Andrea Celli

Found 19 papers, 1 papers with code

A Unifying Framework for Online Optimization with Long-Term Constraints

no code implementations15 Sep 2022 Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Giulia Romano, Nicola Gatti

We present the first best-of-both-world type algorithm for this general class of problems, with no-regret guarantees both in the case in which rewards and constraints are selected according to an unknown stochastic model, and in the case in which they are selected at each round by an adversary.

Management online learning

Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation

no code implementations14 Mar 2022 Brian Zhang, Gabriele Farina, Andrea Celli, Tuomas Sandholm

For team games, the two-sided column generation approach vastly outperforms standard column generation approaches, making it the state of the art algorithm when the parameter is large.

Online Learning with Knapsacks: the Best of Both Worlds

no code implementations28 Feb 2022 Matteo Castiglioni, Andrea Celli, Christian Kroer

We study online learning problems in which a decision maker wants to maximize their expected reward without violating a finite set of $m$ resource constraints.

online learning

Multi-Receiver Online Bayesian Persuasion

no code implementations11 Jun 2021 Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti

Then, we focus on the case of submodular sender's utility functions and we show that, in this case, it is possible to design a polynomial-time no-$(1 - \frac{1}{e})$-regret algorithm.

online learning

Simple Uncoupled No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium

no code implementations4 Apr 2021 Gabriele Farina, Andrea Celli, Alberto Marchesi, Nicola Gatti

The existence of simple uncoupled no-regret learning dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems.

Multi-Agent Coordination in Adversarial Environments through Signal Mediated Strategies

no code implementations9 Feb 2021 Federico Cacciamani, Andrea Celli, Marco Ciccone, Nicola Gatti

Team members can coordinate their strategies before the beginning of the game, but are unable to communicate during the playing phase of the game.

Online Bayesian Persuasion

no code implementations NeurIPS 2020 Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti

We are interested in no-regret algorithms prescribing a signaling scheme at each round of the repeated interaction with performances close to that of the best-in-hindsight signaling scheme.

online learning

Faster Algorithms for Optimal Ex-Ante Coordinated Collusive Strategies in Extensive-Form Zero-Sum Games

no code implementations21 Sep 2020 Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm

Second, we provide an algorithm that computes such an optimal distribution by only using profiles where only one of the team members gets to randomize in each profile.

Signaling in Bayesian Network Congestion Games: the Subtle Power of Symmetry

no code implementations12 Feb 2020 Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti

A natural question is the following: is it possible for an informed sender to reduce the overall social cost via the strategic provision of information to players who update their beliefs rationally?

Public Bayesian Persuasion: Being Almost Optimal and Almost Persuasive

no code implementations12 Feb 2020 Matteo Castiglioni, Andrea Celli, Nicola Gatti

Unlike prior works on this problem, we study the public persuasion problem in the general setting with: (i) arbitrary state spaces; (ii) arbitrary action spaces; (iii) arbitrary sender's utility functions.

Coordination in Adversarial Sequential Team Games via Multi-Agent Deep Reinforcement Learning

no code implementations16 Dec 2019 Andrea Celli, Marco Ciccone, Raffaele Bongo, Nicola Gatti

Many real-world applications involve teams of agents that have to coordinate their actions to reach a common goal against potential adversaries.

reinforcement-learning

Learning to Correlate in Multi-Player General-Sum Sequential Games

1 code implementation NeurIPS 2019 Andrea Celli, Alberto Marchesi, Tommaso Bianchi, Nicola Gatti

In the context of multi-player, general-sum games, there is an increasing interest in solution concepts modeling some form of communication among players, since they can lead to socially better outcomes with respect to Nash equilibria, and may be reached through learning dynamics in a decentralized fashion.

Computer Science and Game Theory

Persuading Voters: It's Easy to Whisper, It's Hard to Speak Loud

no code implementations28 Aug 2019 Matteo Castiglioni, Andrea Celli, Nicola Gatti

In the former, we show that an optimal signaling scheme can be computed efficiently both under a $k$-voting rule and plurality voting.

Bayesian Persuasion with Sequential Games

no code implementations2 Aug 2019 Andrea Celli, Stefano Coniglio, Nicola Gatti

After formalizing the notions of ex ante and ex interim persuasiveness (which differ in the time at which the receivers commit to following the sender's signaling scheme), we investigate the continuous optimization problem of computing a signaling scheme which maximizes the sender's expected revenue.

Computing Optimal Coarse Correlated Equilibria in Sequential Games

no code implementations18 Jan 2019 Andrea Celli, Stefano Coniglio, Nicola Gatti

We investigate the computation of equilibria in extensive-form games where ex ante correlation is possible, focusing on correlated equilibria requiring the least amount of communication between the players and the mediator.

Ex ante coordination and collusion in zero-sum multi-player extensive-form games

no code implementations NeurIPS 2018 Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm

This paper focuses on zero-sum games where a team of players faces an opponent, as is the case, for example, in Bridge, collusion in poker, and many non-recreational applications such as war, where the colluders do not have time or means of communicating during battle, collusion in bidding, where communication during the auction is illegal, and coordinated swindling in public.

Computational Results for Extensive-Form Adversarial Team Games

no code implementations18 Nov 2017 Andrea Celli, Nicola Gatti

We provide, to the best of our knowledge, the first computational study of extensive-form adversarial team games.

Team-maxmin equilibrium: efficiency bounds and algorithms

no code implementations18 Nov 2016 Nicola Basilico, Andrea Celli, Giuseppe De Nittis, Nicola Gatti

The Team-maxmin equilibrium prescribes the optimal strategies for a team of rational players sharing the same goal and without the capability of correlating their strategies in strategic games against an adversary.

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