Search Results for author: Nicola Gatti

Found 38 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

A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving

no code implementations18 Jun 2022 Luca Carminati, Federico Cacciamani, Marco Ciccone, Nicola Gatti

This work shows that we can recover from this weakness by bridging the gap between sequential adversarial team games and 2-player games.

Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts

no code implementations1 Jun 2022 Giulia Romano, Andrea Agostini, Francesco Trovò, Nicola Gatti, Marcello Restelli

We provide two algorithms to address TP-MAB problems, namely, TP-UCB-FR and TP-UCB-EW, which exploit the partial information disclosed by the reward collected over time.

Public Information Representation for Adversarial Team Games

no code implementations25 Jan 2022 Luca Carminati, Federico Cacciamani, Marco Ciccone, Nicola Gatti

Interestingly, we show that our game is more expressive than the original extensive-form game as any state/action abstraction of the extensive-form game can be captured by our representation, while the reverse does not hold.

Exploiting Opponents Under Utility Constraints in Sequential Games

no code implementations NeurIPS 2021 Martino Bernasconi-de-Luca, Federico Cacciamani, Simone Fioravanti, Nicola Gatti, Alberto Marchesi, Francesco Trovò

Recently, game-playing agents based on AI techniques have demonstrated super-human performance in several sequential games, such as chess, Go, and poker.

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.

Trembling-Hand Perfection and Correlation in Sequential Games

no code implementations11 Dec 2020 Alberto Marchesi, Nicola Gatti

After providing an axiomatic definition of EFPCE, we show that one always exists since any perfect (Nash) equilibrium constitutes an EFPCE, and that it is a refinement of EFCE, as any EFPCE is also an EFCE.

Computer Science and Game Theory

Online Posted Pricing with Unknown Time-Discounted Valuations

no code implementations10 Dec 2020 Giulia Romano, Gianluca Tartaglia, Alberto Marchesi, Nicola Gatti

We evaluate our mechanisms in terms of competitive ratio, measuring the worst-case ratio between their revenue and that of an optimal mechanism that knows the distribution of valuations.

Computer Science and Game Theory

Persuading Voters in District-based Elections

no code implementations9 Dec 2020 Matteo Castiglioni, Nicola Gatti

We study both private signaling, in which the sender can use a private communication channel per receiver, and public signaling, in which the sender can use a single communication channel for all the receivers.

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.

Online Joint Bid/Daily Budget Optimization of Internet Advertising Campaigns

no code implementations3 Mar 2020 Alessandro Nuara, Francesco Trovò, Nicola Gatti, Marcello Restelli

We experimentally evaluate our algorithms with synthetic settings generated from real data from Yahoo!, and we present the results of the adoption of our algorithms in a real-world application with a daily average spent of 1, 000 Euros for more than one year.

Gaussian Processes Multiple-choice

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.

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?

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.


Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces

no code implementations18 Nov 2019 Alberto Marchesi, Francesco Trovò, Nicola Gatti

As a result, solving these games begets the challenge of designing learning algorithms that can find (approximate) equilibria with high confidence, using as few simulator queries as possible.

Election Manipulation on Social Networks: Seeding, Edge Removal, Edge Addition

no code implementations14 Nov 2019 Matteo Castiglioni, Nicola Gatti, Giulia Landriani, Diodato Ferraioli

We focus on the election manipulation problem through social influence, where a manipulator exploits a social network to make her most preferred candidate win an election.

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.

Election Manipulation on Social Networks with Messages on Multiple Candidates

no code implementations11 Feb 2019 Matteo Castiglioni, Diodato Ferraioli, Giulia Landriani, Nicola Gatti

We study the problem of election control through social influence when the manipulator is allowed to use the locations that she acquired on the network for sending \emph{both} positive and negative messages on \emph{multiple} candidates, widely extending the previous results available in the literature that study the influence of a single message on a single candidate.

Computer Science and Game Theory

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.

Practical exact algorithm for trembling-hand equilibrium refinements in games

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

Nash equilibrium strategies have the known weakness that they do not prescribe rational play in situations that are reached with zero probability according to the strategies themselves, for example, if players have made mistakes.

Computing the Strategy to Commit to in Polymatrix Games (Extended Version)

no code implementations31 Jul 2018 Giuseppe De Nittis, Alberto Marchesi, Nicola Gatti

We study the computational complexity of finding or approximating an optimistic or pessimistic leader-follower equilibrium in specific classes of succinct games---polymatrix like---which are equivalent to 2-player Bayesian games with uncertainty over the follower, with interdependent or independent types.

Facing Multiple Attacks in Adversarial Patrolling Games with Alarmed Targets

no code implementations19 Jun 2018 Giuseppe De Nittis, Nicola Gatti

We show that even the error of just a single resource can lead to an arbitrary inefficiency, when the inefficiency is defined as the ratio of the Defender's utilities obtained with a wrong guess and a correct guess.

How to Maximize the Spread of Social Influence: A Survey

no code implementations19 Jun 2018 Giuseppe De Nittis, Nicola Gatti

This survey presents the main results achieved for the influence maximization problem in social networks.

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.

Methods for finding leader--follower equilibria with multiple followers

no code implementations7 Jul 2017 Nicola Basilico, Stefano Coniglio, Nicola Gatti

The concept of leader--follower (or Stackelberg) equilibrium plays a central role in a number of real--world applications of game theory.

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.

Unimodal Thompson Sampling for Graph-Structured Arms

no code implementations17 Nov 2016 Stefano Paladino, Francesco Trovò, Marcello Restelli, Nicola Gatti

We study, to the best of our knowledge, the first Bayesian algorithm for unimodal Multi-Armed Bandit (MAB) problems with graph structure.

Multi-resource defensive strategies for patrolling games with alarm systems

no code implementations7 Jun 2016 Nicola Basilico, Giuseppe De Nittis, Nicola Gatti

The central problem with an alarm system, unexplored in other Security Games, is finding the best strategy to respond to alarm signals for each mobile defensive resource.

Adversarial patrolling with spatially uncertain alarm signals

no code implementations9 Jun 2015 Nicola Basilico, Giuseppe De Nittis, Nicola Gatti

That is, the alarm system is able to detect an attack but it is uncertain on the exact position where the attack is taking place.

Cannot find the paper you are looking for? You can Submit a new open access paper.