8 papers
Over-Approximating Minimizer Sets of Constrained Convex Programs with Parametric Uncertainty via Reachability Analysis
Brendan Gould, Chih-Yuan Chiu, Antoine P. Leeman +3
We study the set of solutions to a parameterized, strongly convex optimization problem whose cost depends on uncertain, bounded parameters. We compute a certified outer approximati…
Cost-Matching Model Predictive Control for Efficient Reinforcement Learning in Humanoid Locomotion
Wenqi Cai, Kyriakos G. Vamvoudakis, Sébastien Gros +1
In this paper, we propose a cost-matching approach for optimal humanoid locomotion within a Model Predictive Control (MPC)-based Reinforcement Learning (RL) framework. A parameteri…
Deception Against Data-Driven Linear-Quadratic Control
Filippos Fotiadis, Aris Kanellopoulos, Kyriakos G. Vamvoudakis +1
Deception is a common defense mechanism against adversaries with an information disadvantage. It can force such adversaries to select suboptimal policies for a defender's benefit.…
Tailoring Reproducing Kernels for Optimal Control via Policy Iteration
Shengyuan Niu, Ali Bouland, Haoran Wang +5
This paper presents a novel approach to formulating the actor-critic method for optimal control by casting policy iteration in reproducing kernel Hilbert spaces (RKHSs -- also know…
Quantum Deception: Honey-X Deception using Quantum Games
Efstratios Reppas, Ali Wadi, Brendan Gould +1
In this paper, we develop a framework for deception in quantum games, extending the Honey-X paradigm from classical zero-sum settings into the quantum domain. Building on a view of…
A Novel Framework for Honey-X Deception in Zero-Sum Games
Brendan Gould, Kyriakos Vamvoudakis
In this paper, we present a novel, game-theoretic model of deception in two-player, zero-sum games. Our framework leverages an information asymmetry: one player (the deceiver) has…