16 citations · 42 across the 15 of their papers we have counts for
19 papers
Neural Predictive Monitoring under Partial Observability
Francesca Cairoli, Luca Bortolussi, Nicola Paoletti
We consider the problem of predictive monitoring (PM), i.e., predicting at runtime future violations of a system from the current state. We work under the most realistic settings w…
Certification of Iterative Predictions in Bayesian Neural Networks
Matthew Wicker, Luca Laurenti, Andrea Patane +3
We consider the problem of computing reach-avoid probabilities for iterative predictions made with Bayesian neural network (BNN) models. Specifically, we leverage bound propagation…
On Guaranteed Optimal Robust Explanations for NLP Models
Emanuele La Malfa, Agnieszka Zbrzezny, Rhiannon Michelmore +2
We build on abduction-based explanations for ma-chine learning and develop a method for computing local explanations for neural network models in natural language processing (NLP).…
Learnable Strategies for Bilateral Agent Negotiation over Multiple Issues
Pallavi Bagga, Nicola Paoletti, Kostas Stathis
We present a novel bilateral negotiation model that allows a self-interested agent to learn how to negotiate over multiple issues in the presence of user preference uncertainty. Th…
MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas
Hongkai Chen, Nicola Paoletti, Scott A. Smolka +1
Even though model predictive control (MPC) is currently the main algorithm for insulin control in the artificial pancreas (AP), it usually requires complex online optimizations, wh…
A Deep Reinforcement Learning Approach to Concurrent Bilateral Negotiation
Pallavi Bagga, Nicola Paoletti, Bedour Alrayes +1
We present a novel negotiation model that allows an agent to learn how to negotiate during concurrent bilateral negotiations in unknown and dynamic e-markets. The agent uses an act…
Neural Simplex Architecture
Dung T. Phan, Radu Grosu, Nils Jansen +3
We present the Neural Simplex Architecture (NSA), a new approach to runtime assurance that provides safety guarantees for neural controllers (obtained e.g. using reinforcement lear…
Statistical Guarantees for the Robustness of Bayesian Neural Networks
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti +3
We introduce a probabilistic robustness measure for Bayesian Neural Networks (BNNs), defined as the probability that, given a test point, there exists a point within a bounded set…
Automated Synthesis of Safe Digital Controllers for Sampled-Data Stochastic Nonlinear Systems
Fedor Shmarov, Sadegh Soudjani, Nicola Paoletti +4
We present a new method for the automated synthesis of digital controllers with formal safety guarantees for systems with nonlinear dynamics, noisy output measurements, and stochas…
Neural State Classification for Hybrid Systems
Dung Phan, Nicola Paoletti, Timothy Zhang +3
We introduce the State Classification Problem (SCP) for hybrid systems, and present Neural State Classification (NSC) as an efficient solution technique. SCP generalizes the model…
How to Learn a Model Checker
Dung Phan, Radu Grosu, Nicola Paoletti +2
We show how machine-learning techniques, particularly neural networks, offer a very effective and highly efficient solution to the approximate model-checking problem for continuous…
Declarative vs Rule-based Control for Flocking Dynamics
Usama Mehmood, Nicola Paoletti, Dung Phan +6
The popularity of rule-based flocking models, such as Reynolds' classic flocking model, raises the question of whether more declarative flocking models are possible. This question…
Automated Synthesis of Safe and Robust PID Controllers for Stochastic Hybrid Systems
Fedor Shmarov, Nicola Paoletti, Ezio Bartocci +3
We present a new method for the automated synthesis of safe and robust Proportional-Integral-Derivative (PID) controllers for stochastic hybrid systems. Despite their widespread us…
Data-Driven Robust Control for Type 1 Diabetes Under Meal and Exercise Uncertainties
Nicola Paoletti, Kin Sum Liu, Scott A. Smolka +1
We present a fully closed-loop design for an artificial pancreas (AP) which regulates the delivery of insulin for the control of Type I diabetes. Our AP controller operates in a fu…
Estimation and Modelling of PCBs Bioaccumulation in the Adriatic Sea Ecosystem
Marianna Taffi, Nicola Paoletti, Pietro Liò +3
Persistent Organic Pollutants represent a global ecological concern due to their ability to accumulate in organisms and to spread species-by-species via feeding connections. In thi…
Adaptability Checking in Multi-Level Complex Systems
Emanuela Merelli, Nicola Paoletti, Luca Tesei
A hierarchical model for multi-level adaptive systems is built on two basic levels: a lower behavioural level B accounting for the actual behaviour of the system and an upper struc…
A multi-level model for self-adaptive systems
Emanuela Merelli, Nicola Paoletti, Luca Tesei
This work introduces a general multi-level model for self-adaptive systems. A self-adaptive system is seen as composed by two levels: the lower level describing the actual behaviou…
Disease processes as hybrid dynamical systems
Pietro Liò, Emanuela Merelli, Nicola Paoletti
We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understand…
Multiple verification in computational modeling of bone pathologies
Pietro Liò, Emanuela Merelli, Nicola Paoletti
We introduce a model checking approach to diagnose the emerging of bone pathologies. The implementation of a new model of bone remodeling in PRISM has led to an interesting charact…