29 citations · 160 across the 58 of their papers we have counts for
7 papers · 1 filter
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…
Learning Robust Policies for Uncertain Parametric Markov Decision Processes
Luke Rickard, Alessandro Abate, Kostas Margellos
Synthesising verifiably correct controllers for dynamical systems is crucial for safety-critical problems. To achieve this, it is important to account for uncertainty in a robust m…
Homomorphically encrypted gradient descent algorithms for quadratic programming
André Bertolace, Konstantinos Gatsis, Kostas Margellos
In this paper, we evaluate the different fully homomorphic encryption schemes, propose an implementation, and numerically analyze the applicability of gradient descent algorithms t…
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…
Distributed Safe Control Design and Probabilistic Safety Verification for Multi-Agent Systems
Han Wang, Antonis Papachristodoulou, Kostas Margellos
We propose distributed iterative algorithms for safe control design and safety verification for networked multi-agent systems. These algorithms rely on distributing a control barri…
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…