426 citations · 651 across the 43 of their papers we have counts for
46 papers
Advanced monitoring of rail breakage in double-track railway lines by means of PCA techniques
F. Espinosa, J. J. García, A. Hernández +6
This work describes a classifier designed to identify rail breakages in double-track railway lines, completing the electronic equipment carried out by authors. The main objective o…
Data-driven Abstractions for Verification of Deterministic Systems
Rudi Coppola, Andrea Peruffo, Manuel Mazo
A common technique to verify complex logic specifications for dynamical systems is the construction of symbolic abstractions: simpler, finite-state models whose behaviour mimics th…
Interval Markov Decision Processes with Continuous Action-Spaces
Giannis Delimpaltadakis, Morteza Lahijanian, Manuel Mazo +1
Interval Markov Decision Processes (IMDPs) are finite-state uncertain Markov models, where the transition probabilities belong to intervals. Recently, there has been a surge of res…
Bounded Robustness in Reinforcement Learning via Lexicographic Objectives
Daniel Jarne Ornia, Licio Romao, Lewis Hammond +2
Policy robustness in Reinforcement Learning may not be desirable at any cost: the alterations caused by robustness requirements from otherwise optimal policies should be explainabl…
Robust Event-Driven Interactions in Cooperative Multi-Agent Learning
Daniel Jarne Ornia, Manuel Mazo
We present an approach to reduce the communication required between agents in a Multi-Agent learning system by exploiting the inherent robustness of the underlying Markov Decision…
Data-driven Abstractions with Probabilistic Guarantees for Linear PETC Systems
Andrea Peruffo, Manuel Mazo
We employ the scenario approach to compute probably approximately correct (PAC) bounds on the average inter-sample time (AIST) generated by an unknown PETC system, based on a finit…