10 citations · 24 across the 13 of their papers we have counts for
8 papers · 1 filter
A Prediction-Correction Algorithm for Real-Time Model Predictive Control
Santiago Paternain, Manfred Morari, Alejandro Ribeiro
In this work we adapt a prediction-correction algorithm for continuous time-varying convex optimization problems to solve dynamic programs arising from Model Predictive Control. In…
Safe Policies for Reinforcement Learning via Primal-Dual Methods
Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon +1
In this paper, we study the learning of safe policies in the setting of reinforcement learning problems. This is, we aim to control a Markov Decision Process (MDP) of which we do n…
Constrained Reinforcement Learning Has Zero Duality Gap
Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana +1
Autonomous agents must often deal with conflicting requirements, such as completing tasks using the least amount of time/energy, learning multiple tasks, or dealing with multiple o…
Source Seeking in Unknown Environments with Convex Obstacles
Bruno A. Angélico, Luiz F. O. Chamon, Santiago Paternain +2
Navigation tasks often cannot be defined in terms of a target, either because global position information is unavailable or unreliable or because target location is not explicitly…
Navigation of a Quadratic Potential with Ellipsoidal Obstacles
Harshat Kumar, Santiago Paternain, Alejandro Ribeiro
Given a convex quadratic potential of which its minimum is the agent's goal and a Euclidean space populated with ellipsoidal obstacles, one can construct a Rimon-Koditschek (RK) ar…
Sparse multiresolution representations with adaptive kernels
Maria Peifer, Luiz. F. O. Chamon, Santiago Paternain +1
Reproducing kernel Hilbert spaces (RKHSs) are key elements of many non-parametric tools successfully used in signal processing, statistics, and machine learning. In this work, we a…