29 citations · 160 across the 58 of their papers we have counts for
39 papers · 1 filter
On the suboptimality of stochastic MPC with varying constraint horizon
Allan Andre Do Nascimento, Andre Bertolace, Antonis Papachristodoulou +1
Enforcing stochastic state constraints over the full prediction horizon in Model Predictive Control (MPC) can be computationally demanding. Here we study stochastic MPC without ter…
Efficient Quantification of Time-Series Prediction Error: Optimal Selection Conformal Prediction
Boyu Pang, Kostas Margellos
Designing effective score functions in Conformal Prediction (CP) for time-series data remains challenging due to conservativeness and/or computational inefficiency. We propose Opti…
Data-Driven Performance Guarantees for Parametric Optimization Problems
Jingyi Huang, Paul Goulart, Kostas Margellos
We propose a data-driven method to establish probabilistic performance guarantees for parametric optimization problems solved via iterative algorithms. Our approach addresses two k…
Predictive Control Barrier Functions: Bridging model predictive control and control barrier functions
Jingyi Huang, Han Wang, Kostas Margellos +1
In this paper, we establish a connection between model predictive control (MPC) techniques and Control Barrier Functions (CBFs). Recognizing the similarity between CBFs and Control…
Finite sample learning of moving targets
Nikolaus Vertovec, Kostas Margellos, Maria Prandini
We consider a moving target that we seek to learn from samples. Our results extend randomized techniques developed in control and optimization for a constant target to the case whe…
Convex Co-Design of Control Barrier Function and Safe Feedback Controller Under Input Constraints
Han Wang, Kostas Margellos, Antonis Papachristodoulou +1
We study the problem of co-designing control barrier functions (CBF) and linear state feedback controllers for continuous-time linear systems. We achieve this by means of a single…
Probably approximately correct stability of allocations in uncertain coalitional games with private sampling
George Pantazis, Filiberto Fele, Filippo Fabiani +2
We study coalitional games with exogenous uncertainty in the coalition value, in which each agent is allowed to have private samples of the uncertainty. As a consequence, the agent…
A priori data-driven robustness guarantees on strategic deviations from generalised Nash equilibria
George Pantazis, Filiberto Fele, Kostas Margellos
In this paper we focus on noncooperative games with uncertain constraints coupling the agents' decisions. We consider a setting where bounded deviations of agents' decisions from t…
Distributionally robust stability of payoff allocations in stochastic coalitional games
George Pantazis, Barbara Franci, Sergio Grammatico +1
We consider multi-agent coalitional games with uncertainty in the coalitional values. We provide a novel methodology to study the stability of the grand coalition in the case where…
State Aggregation for Distributed Value Iteration in Dynamic Programming
Nikolaus Vertovec, Kostas Margellos
We propose a distributed algorithm to solve a dynamic programming problem with multiple agents, where each agent has only partial knowledge of the state transition probabilities an…
Safe Controlled Invariance for Linear Systems Using Sum-of-Squares Programming
Han Wang, Kostas Margellos, Antonis Papachristodoulou
Safety is closely related to set invariance for dynamical systems. However, synthesizing a safe invariant set and at the same time synthesizing the associated safe controller still…
A Time-Triggered Dimension Reduction Algorithm for the Task Assignment Problem
Han Wang, Kostas Margellos, Antonis Papachristodoulou
The task assignment problem is fundamental in combinatorial optimisation, aiming at allocating one or more tasks to a number of agents while minimizing the total cost or maximizing…
Safety Verification and Controller Synthesis for Systems with Input Constraints
Han Wang, Kostas Margellos, Antonis Papachristodoulou
In this paper we consider the safety verification and safe controller synthesis problems for nonlinear control systems. The Control Barrier Certificates (CBC) approach is proposed…
Explicit Solutions for Safety Problems Using Control Barrier Functions
Han Wang, Kostas Margellos, Antonis Papachristodoulou
The control Barrier function approach has been widely used for safe controller synthesis. By solving an online convex quadratic programming problem, an optimal safe controller can…
Probabilistically robust stabilizing allocations in uncertain coalitional games
George Pantazis, Filippo Fabiani, Filiberto Fele +1
In this paper we consider multi-agent coalitional games with uncertain value functions for which we establish distribution-free guarantees on the probability of allocation stabilit…
On the sensitivity of linear resource sharing problems to the arrival of new agents
Alessandro Falsone, Kostas Margellos, Jacopo Zizzo +2
We consider a multi-agent optimal resource sharing problem that is represented by a linear program. The amount of resource to be shared is fixed, and agents belong to a population…
Probabilistic stabilizability certificates for a class of black-box linear systems
Filippo Fabiani, Kostas Margellos, Paul J. Goulart
We provide out-of-sample certificates on the controlled invariance property of a given set with respect to a class of black-box linear systems. Specifically, we consider linear tim…
Multi-objective minimum time optimal control for low-thrust trajectory design
Nikolaus Vertovec, Sina Ober-Blöbaum, Kostas Margellos
We propose a reachability approach for infinite and finite horizon multi-objective optimization problems for low-thrust spacecraft trajectory design. The main advantage of the prop…
On the probabilistic feasibility of solutions in multi-agent optimization problems under uncertainty
George Pantazis, Filiberto Fele, Kostas Margellos
We investigate the probabilistic feasibility of randomized solutions to two distinct classes of uncertain multi-agent optimization programs. We first assume that only the constrain…
Approximate Dynamic Programming for Delivery Time Slot Pricing: a Sensitivity Analysis
Denis Lebedev, Kostas Margellos, Paul Goulart
We consider the revenue management problem of finding profit-maximising prices for delivery time slots in the context of attended home delivery. This multi-stage optimal control pr…
Gradient-Bounded Dynamic Programming for Submodular and Concave Extensible Value Functions with Probabilistic Performance Guarantees
Denis Lebedev, Paul Goulart, Kostas Margellos
We consider stochastic dynamic programming problems with high-dimensional, discrete state-spaces and finite, discrete-time horizons that prohibit direct computation of the value fu…
Gradient-Bounded Dynamic Programming with Submodular and Concave Extensible Value Functions
Denis Lebedev, Paul Goulart, Kostas Margellos
We consider dynamic programming problems with finite, discrete-time horizons and prohibitively high-dimensional, discrete state-spaces for direct computation of the value function…
On the robustness of equilibria in generalized aggregative games
Filippo Fabiani, Kostas Margellos, Paul J. Goulart
We address the problem of assessing the robustness of the equilibria in uncertain, multi-agent games. Specifically, we focus on generalized Nash equilibrium problems in aggregative…
Probabilistic feasibility guarantees for solution sets to uncertain variational inequalities
Filippo Fabiani, Kostas Margellos, Paul J. Goulart
We develop a data-driven approach to the computation of a-posteriori feasibility certificates to the solution sets of variational inequalities affected by uncertainty. Specifically…