13 citations · 19 across the 11 of their papers we have counts for
18 papers
Strategically Robust Game-Theoretic Multi-Agent Trajectory Optimization
Victor L. Qin, Nicolas Lanzetti, Saverio Bolognani +1
Aviation authorities worldwide expect Advanced Air Mobility (AAM) traffic management to be decentralized among service providers, requiring AAM flights to autonomously plan traject…
Strategically Robust Aggregative Games
Andreas Feik, Nicolas Lanzetti, Saverio Bolognani +2
In many multiagent settings, such as electric vehicle charging and traffic routing, agents must make decisions in the face of uncertain behavior exhibited by others. Often, this un…
Sparse optimal control in the Wasserstein space
Enrico Sartor, Florian Dörfler, Nicolas Lanzetti
We study sparse optimal control of a non-local continuity equation, where the goal is to steer a distribution via finitely many controllable agents or actuators. This model arises…
Hedging against Black Swans in Day-Ahead Energy Markets
Liviu Aolaritei, Boubacar Bangoura, Saverio Bolognani +2
Renewable generators must commit to day-ahead market bids despite uncertainty in both production and real-time prices. While forecasts provide valuable guidance, rare and unpredict…
Strategically Robust Game Theory via Optimal Transport
Nicolas Lanzetti, Sylvain Fricker, Saverio Bolognani +2
In many game-theoretic settings, agents are challenged with taking decisions against the uncertain behavior exhibited by others. Often, this uncertainty arises from multiple source…
Gradient-flow SDEs have unique transient population dynamics
Vincent Guan, Joseph Janssen, Nicolas Lanzetti +3
Identifying the drift and diffusion of an SDE from its population dynamics is a notoriously challenging task. Researchers in machine learning and single-cell biology have only been…
Distributionally Robust Linear Quadratic Gaussian Regulator with Stationary Distributions
Alain Schöbi, Nicolas Lanzetti, Florian Dörfler +2
We study the Linear Quadratic Gaussian regulation problem in the face of worst-case noise distributions when these are mutually independent, zero-mean, stationary, and within a rad…
Fairness in Social Influence Maximization via Optimal Transport
Shubham Chowdhary, Giulia De Pasquale, Nicolas Lanzetti +2
We study fairness in social influence maximization, whereby one seeks to select seeds that spread a given information throughout a network, ensuring balanced outreach among differe…
Learning diffusion at lightspeed
Antonio Terpin, Nicolas Lanzetti, Martin Gadea +1
Diffusion regulates numerous natural processes and the dynamics of many successful generative models. Existing models to learn the diffusion terms from observational data rely on c…
Variational Analysis in the Wasserstein Space
Nicolas Lanzetti, Antonio Terpin, Florian Dörfler
We study optimization problems whereby the optimization variable is a probability measure. Since the space of probability measures is not a vector space, many classical methods for…
The Impact of Recommendation Systems on Opinion Dynamics: Microscopic versus Macroscopic Effects
Nicolas Lanzetti, Florian Dörfler, Nicolò Pagan
Recommendation systems are widely used in web services, such as social networks and e-commerce platforms, to serve personalized content to the users and, thus, enhance their experi…
Capture, Propagate, and Control Distributional Uncertainty
Liviu Aolaritei, Nicolas Lanzetti, Florian Dörfler
We study stochastic dynamical systems in settings where only partial statistical information about the noise is available, e.g., in the form of a limited number of noise realizatio…
Dynamic Programming in Probability Spaces via Optimal Transport
Antonio Terpin, Nicolas Lanzetti, Florian Dörfler
We study discrete-time finite-horizon optimal control problems in probability spaces, whereby the state of the system is a probability measure. We show that, in many instances, the…
Stochastic Wasserstein Gradient Flows using Streaming Data with an Application in Predictive Maintenance
Nicolas Lanzetti, Efe C. Balta, Dominic Liao-McPherson +1
We study estimation problems in safety-critical applications with streaming data. Since estimation problems can be posed as optimization problems in the probability space, we devis…
Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions
Antonio Terpin, Nicolas Lanzetti, Batuhan Yardim +2
Policy Optimization (PO) algorithms have been proven particularly suited to handle the high-dimensionality of real-world continuous control tasks. In this context, Trust Region Pol…
Modeling of Political Systems using Wasserstein Gradient Flows
Nicolas Lanzetti, Joudi Hajar, Florian Dörfler
The study of complex political phenomena such as parties' polarization calls for mathematical models of political systems. In this paper, we aim at modeling the time evolution of a…
First-order Conditions for Optimization in the Wasserstein Space
Nicolas Lanzetti, Saverio Bolognani, Florian Dörfler
We study first-order optimality conditions for constrained optimization in the Wasserstein space, whereby one seeks to minimize a real-valued function over the space of probability…
Distributional Uncertainty Propagation via Optimal Transport
Liviu Aolaritei, Nicolas Lanzetti, Hongruyu Chen +1
This paper addresses the limitations of standard uncertainty models, e.g., robust (norm-bounded) and stochastic (one fixed distribution, e.g., Gaussian), and proposes to model unce…