Deliverables

D1.1: Artificial Intelligent system key specifications

Editors: Federico Oliva and Corrado Possieri, WP1, Jul. 2022.

Public Deliverable. Email us and request it.

D1.2: Epidemic modeling and optimisation parameters

Editors: Federico Oliva and Corrado Possieri, WP1, Dec. 2022.

Public Deliverable. Email us and request it.

D2.1: Systematic review of evidence on the transmission index of SARS-CoV-2

Editors: Roberta Pastorino, WP2, Jul. 2022.

Public Deliverable. Email us and request it.

D2.2: Transmission index of SARS-CoV-2 in different environmental and urban settings

Editors: Cosimo Savoia, WP2, Nov. 2022.

Public Deliverable. Email us and request it.

D3.1: Report on simulation environments with assessment of their adequacy to represent the spread of an epidemic

Editors:Deborah Hugon, WP3, May 2022.

Internal Deliverable.

D3.2: Virtual environment to determine the spread of SARS-CoV-2 given the topology of an urban area and the behavioural logic for the individuals

Editors: Deborah Hugon, WP3, Dec. 2022.

Internal Deliverable.

D3.3: Report of the simulator validation

Editors: Eduardo De Los Santos, WP3, Nov. 2023.

Public Deliverable. Email us and request it.

D4.1: Review on different techniques of explainable AI and reinforcement learning

Editors:Alessia Paglialonga and Maurizio Mongelli, WP4, Jul 2022.

Public Deliverable. Email us and request it.

D4.2: Modeling of crowd behavioral logics in critical infrastructure

Editors: Corrado Possieri and Federico Oliva, WP4, Dec. 2022.

Public Deliverable. Email us and request it.

D4.3: Software Implementation of Reinforcement Learning Tabular Methods for Behavioral Policy Design

Editors: Federico Oliva and Corrado Possieri, WP4, Nov. 2023.

Public Deliverable. Email us and request it.

D5.1: Testing and Formal Verification of Software with Learning-Enabled Components

Editors: Emanuele De Angelis, WP5, Jul. 2022.

Public Deliverable. Email us and request it.

D5.2: Testing and Formal Verification of Rule-based Decision Support Systems

Editors: Emanuele De Angelis, WP5, Dec. 2022.

Public Deliverable. Email us and request it.

D5.3: A CLP-based tool for analyzing rule-based XAI models

Editors: Emanuele De Angelis, WP5, Nov. 2023.

Public Deliverable. Email us and request it.

D6.1: OPENNESS dissemination and diffusion plan

Editors: Corrado Possieri, WP6, Jul. 2022.

Public Deliverable. Email us and request it.

D6.2: Project's Dissemination Artefacts

Editors: Maurizio Proietti, WP6, Jun. 2022.

Public Deliverable. Email us and request it.

D6.3: Project's Dissemination Activities

Editors: Maurizio Proietti, WP6, Nov. 2023.

Public Deliverable. Email us and request it.

D7.1: Project's Meetings Reports -- First Period

Editors: Guglielmo De Angelis, WP7, Jun. 2022.

Internal Deliverable.

D7.1: Project's Meetings Reports -- Second Period

Editors: Guglielmo De Angelis, WP7, Nov. 2023.

Internal Deliverable.

D7.2: Ethical Recommendations - A few remarks on the activities in OPENNESS

Editors: Guglielmo De Angelis, WP7, Nov. 2023.

Public Deliverable. Email us and request it.

Publications


Reachability analysis in stochastic directed graphs by reinforcement learning.

Corrado Possieri, Mattia Frasca, and Alessandro Rizzo. IEEE Transactions on Automatic Control, 2022.

Q-learning for continuous-time linear systems: A data-driven implementation of the Kleinman algorithm.

Corrado Possieri and Mario Sassano. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022.

Data-driven policy iteration for nonlinear optimal control problems.

Corrado Possieri and Mario Sassano. IEEE Transactions on Neural Networks and Learning Systems, 2022.


On the use of the time-integrals of the output in observer design for nonlinear autonomous systems.

Laura Menini, Corrado Possieri, and Antonio Tornambe. IEEE Transactions on Automatic Control, 67(1):336--343, 2022.

Design of high-gain observers based on sampled measurements via the interval arithmetic.

Laura Menini, Corrado Possieri, and Antonio Tornambe. Automatica, 131:109741, 2021.

A classification study on testing and verification of AI-based systems.

Emanuele De Angelis, Guglielmo De Angelis, and Maurizio Proietti. Proc. of the International Conference On Artificial Intelligence Testing (AITest), pages 1--8. IEEE, 2023.


Parameters in mathematical modelling of indoor spread of covid-19: a scoping review.

Cosimo Savoia, Roberta Pastorino, Angelo Maria Pezzullo, and Stefania Boccia. Abstract in Proc. of the 17th World Congress on Public Health, number A392, 2023

Modelli matematici volti a ostacolare la tramissione delle infezioni in ambienti indoor: Lezioni dal covid-19.

Cosimo Savoia, Angelo Maria Pezzullo, Roberta Pastorino, and Stefania Boccia. Abstract in Proc. of the 56th National Congress of the Società Italiana di Igiene, Medicina Preventiva e Sanità Pubblica (SItI), number A90934, 2023.

Individual-level exposures and risk of COVID-19: an umbrella review.

Cosimo Savoia, Angelo Maria Pezzullo, Sara Farina, Diego Maria Tona, Matteo Di Pumpo, Martina Porcelli, and Stefania Boccia. Abstract in of the European Conference of Public Health, number A392, 2023.

Value iteration via output feedback for LQ optimal control of SISO systems.

Corrado Possieri. In Proc. of the International Federation of Automatic Control World Congress (IFAC) 2023.

Presentations

Impact At IASI 2022-10-21

Projetc Overview

Impact @ IASI

21st Oct. 2022

Guglielmo De Angelis

Research Seminar at UCSC 2022-09-19

OPENNESS: OPtimal bEhavior iN paNdEmic ScenarioS

Research Seminar at UCSC

19th Sep. 2022

Cosimo Savoia

Yes At IASI 2022-11-10

Loads of people and a bit of COVID: Infection reduction in critical infrastructures

Yes @ IASI

10th Nov. 2022

Federico Oliva

Impact At IASI 2023-03-30

Rule-based model of the risk of SARS-CoV-2 infection spread in indoor environments

Impact @ IASI

30th Mar. 2023

Eduardo De Los Santos

Poster

OPENNESS Official Poster

PNG, High Resolution

OPENNESS Official Poster

PDF, Flyer Version

Other Resources

OPENNESS on the magazine Scenari

OPENNESS on the issue N. 10/2022 of the magazine "Scenari: Le Aziende Informano"

PDF (excerpt)