426 citations · 651 across the 43 of their papers we have counts for
9 papers · 1 filter
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…
ETCetera: beyond Event-Triggered Control
Giannis Delimpaltadakis, Gabriel de A. Gleizer, Ivo van Straalen +1
We present ETCetera, a Python library developed for the analysis and synthesis of the sampling behaviour of event triggered control (ETC) systems. In particular, the tool construct…