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<!DOCTYPE HTML>
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<title>OPENNESS: OPtimal bEhavior iN paNdEmic ScenarioS</title>
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<h2>OPENNESS</h2>
<p>OPtimal bEhavior iN paNdEmic ScenarioS</p>
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<section class="box" id="d1.1">
<!-- <a href="#" class="image featured"><img src="images/pic02.jpg" alt="" /></a> -->
<header>
<h3>D1.1: Artificial Intelligent system key specifications</h3>
</header>
<p><em>Editors:</em> Federico Oliva and Corrado Possieri, WP1, Jul. 2022.</p>
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Public Deliverable. Email us and request it.
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<h3>D1.2: Epidemic modeling and optimisation parameters</h3>
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<p><em>Editors:</em> Federico Oliva and Corrado Possieri, WP1, Dec. 2022.</p>
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<h3>D2.1: Systematic review of evidence on the transmission index of SARS-CoV-2</h3>
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<p><em>Editors:</em> Roberta Pastorino, WP2, Jul. 2022.</p>
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<h3>D2.2: Transmission index of SARS-CoV-2 in different environmental and urban settings</h3>
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<p><em>Editors:</em> Cosimo Savoia, WP2, Nov. 2022.</p>
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Public Deliverable. Email us and request it.
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<h3>D3.1: Report on simulation environments with assessment of their adequacy to represent the spread of an epidemic</h3>
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<p><em>Editors:</em>Deborah Hugon, WP3, May 2022.</p>
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Internal Deliverable.
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<h3>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</h3>
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<p><em>Editors:</em> Deborah Hugon, WP3, Dec. 2022.</p>
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Internal Deliverable.
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<h3>D3.3: Report of the simulator validation</h3>
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<p><em>Editors:</em> Eduardo De Los Santos, WP3, Nov. 2023.</p>
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<h3>D4.1: Review on different techniques of explainable AI and reinforcement learning</h3>
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<p><em>Editors:</em>Alessia Paglialonga and Maurizio Mongelli, WP4, Jul 2022.</p>
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<h3>D4.2: Modeling of crowd behavioral logics in critical infrastructure</h3>
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<p><em>Editors:</em> Corrado Possieri and Federico Oliva, WP4, Dec. 2022.</p>
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<h3>D4.3: Software Implementation of Reinforcement Learning Tabular Methods for Behavioral Policy Design</h3>
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<p><em>Editors:</em> Federico Oliva and Corrado Possieri, WP4, Nov. 2023.</p>
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<h3>D5.1: Testing and Formal Verification of Software with Learning-Enabled Components</h3>
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<p><em>Editors:</em> Emanuele De Angelis, WP5, Jul. 2022.</p>
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<h3>D5.2: Testing and Formal Verification of Rule-based Decision Support Systems</h3>
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<p><em>Editors:</em> Emanuele De Angelis, WP5, Dec. 2022.</p>
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<h3>D5.3: A CLP-based tool for analyzing rule-based XAI models</h3>
</header>
<p><em>Editors:</em> Emanuele De Angelis, WP5, Nov. 2023.</p>
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<section class="box" id="d6.1">
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<h3>D6.1: OPENNESS dissemination and diffusion plan</h3>
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<p><em>Editors:</em> Corrado Possieri, WP6, Jul. 2022.</p>
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<h3>D6.2: Project's Dissemination Artefacts</h3>
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<p><em>Editors:</em> Maurizio Proietti, WP6, Jun. 2022.</p>
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<h3>D6.3: Project's Dissemination Activities</h3>
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<p><em>Editors:</em> Maurizio Proietti, WP6, Nov. 2023.</p>
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<h3>D7.1: Project's Meetings Reports -- First Period</h3>
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<p><em>Editors:</em> Guglielmo De Angelis, WP7, Jun. 2022.</p>
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Internal Deliverable.
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<section class="box" id="d7.1-bis">
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<header>
<h3>D7.1: Project's Meetings Reports -- Second Period</h3>
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<p><em>Editors:</em> Guglielmo De Angelis, WP7, Nov. 2023.</p>
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Internal Deliverable.
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<h3>D7.2: Ethical Recommendations - A few remarks on the activities in OPENNESS</h3>
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<p><em>Editors:</em> Guglielmo De Angelis, WP7, Nov. 2023.</p>
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<h3></h3>
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<p><em>Editors:</em>, WPX, 2022.</p>
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<h3>Reachability analysis in stochastic directed graphs by reinforcement learning.</h3>
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<p>Corrado Possieri, Mattia Frasca, and Alessandro Rizzo. <em>IEEE Transactions on Automatic Control</em>, 2022.</p>
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<h3>Q-learning for continuous-time linear systems: A data-driven implementation of the Kleinman algorithm.</h3>
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<p>Corrado Possieri and Mario Sassano. <em>IEEE Transactions on Systems, Man, and Cybernetics: Systems</em>, 2022.</p>
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<h3>Data-driven policy iteration for nonlinear optimal control problems.</h3>
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<p>Corrado Possieri and Mario Sassano. <em>IEEE Transactions on Neural Networks and Learning Systems</em>, 2022.</p>
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<h3>On the use of the time-integrals of the output in observer design for nonlinear autonomous systems.</h3>
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<p>Laura Menini, Corrado Possieri, and Antonio Tornambe. <em>IEEE Transactions on Automatic Control</em>, 67(1):336--343, 2022.</p>
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<h3>Design of high-gain observers based on sampled measurements via the interval arithmetic.</h3>
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<p>Laura Menini, Corrado Possieri, and Antonio Tornambe. <em>Automatica</em>, 131:109741, 2021.</p>
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