39 citations · 57 across the 17 of their papers we have counts for
3 papers · 1 filter
Data-driven memory-dependent abstractions of dynamical systems
Adrien Banse, Licio Romao, Alessandro Abate +1
We propose a sample-based, sequential method to abstract a (potentially black-box) dynamical system with a sequence of memory-dependent Markov chains of increasing size. We show th…
Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty
Thom Badings, Licio Romao, Alessandro Abate +1
Capturing uncertainty in models of complex dynamical systems is crucial to designing safe controllers. Stochastic noise causes aleatoric uncertainty, whereas imprecise knowledge of…
LCRL: Certified Policy Synthesis via Logically-Constrained Reinforcement Learning
Hosein Hasanbeig, Daniel Kroening, Alessandro Abate
LCRL is a software tool that implements model-free Reinforcement Learning (RL) algorithms over unknown Markov Decision Processes (MDPs), synthesising policies that satisfy a given…