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513 results on '"Vallati, Mauro"'

103. pMineR: An Innovative R Library for Performing Process Mining in Medicine

Author

Gatta, Roberto, primary, Lenkowicz, Jacopo, additional, Vallati, Mauro, additional, Rojas, Eric, additional, Damiani, Andrea, additional, Sacchi, Lucia, additional, De Bari, Berardino, additional, Dagliati, Arianna, additional, Fernandez-Llatas, Carlos, additional, Montesi, Matteo, additional, Marchetti, Antonio, additional, Castellano, Maurizio, additional, and Valentini, Vincenzo, additional

Published
2017
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104. Improving Domain-Independent Heuristic State-Space Planning via plan cost predictions.

Author

Percassi, Francesco, Gerevini, Alfonso E., Scala, Enrico, Serina, Ivan, and Vallati, Mauro

Subjects
ARTIFICIAL intelligence, HEURISTIC, AUTOMATED planning & scheduling, MACHINE learning, FORECASTING
Abstract

Automated planning is a prominent Artificial Intelligence (AI) challenge that has been extensively studied for decades, which has led to the development of powerful domain-independent planning systems. The performance of domain-independent planning systems are strongly affected by the structure of the search space, that is dependent on the application domain and on its encoding. This paper proposes and investigates a novel way of combining machine learning and heuristic search to improve domain-independent planning. On the learning side, we use learning to predict the plan cost of a good solution for a given instance. On the planning side, we propose a bound-sensitive heuristic function that exploits such a prediction in a state-space planner. Our function combines the input prediction (derived inductively) with some pieces of information gathered during search (derived deductively). As the prediction can sometimes be grossly inaccurate, the function also provides means to recognise when the provided information is actually misguiding the search. Our experimental analysis demonstrates the usefulness of the proposed approach in a standard heuristic best-first search schema. [ABSTRACT FROM AUTHOR]

Published
2023
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109. On the Configuration of More and Less Expressive Logic Programs.

Author

DODARO, CARMINE, MARATEA, MARCO, and VALLATI, MAURO

Subjects
LOGIC, ARTIFICIAL intelligence, MATHEMATICAL reformulation
Abstract

The decoupling between the representation of a certain problem, that is, its knowledge model, and the reasoning side is one of main strong points of model-based artificial intelligence (AI). This allows, for example, to focus on improving the reasoning side by having advantages on the whole solving process. Further, it is also well known that many solvers are very sensitive to even syntactic changes in the input. In this paper, we focus on improving the reasoning side by taking advantages of such sensitivity. We consider two well-known model-based AI methodologies, SAT and ASP, define a number of syntactic features that may characterise their inputs, and use automated configuration tools to reformulate the input formula or program. Results of a wide experimental analysis involving SAT and ASP domains, taken from respective competitions, show the different advantages that can be obtained by using input reformulation and configuration. [ABSTRACT FROM AUTHOR]

Published
2023
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124. The 2014 International Planning Competition: progress and trends

Author

Vallati, Mauro, Chrpa, Lukas, Grzes, Marek, McCluskey, Thomas L., Roberts, Mark, and Sanner, Scott

Subjects
Artificial intelligence -- Methods, Contests -- Methods, Planning -- Technology application, Business
Abstract

This article reviews the 2014 International Planning Competition (IPC-2014), the eighth in a series of competitions starting in 1998. IPC-2014 was held in three separate parts to assess the state [...]

Published
2015

125. The Fifth International Competition on Knowledge engineering for planning and scheduling: summary and trends

Author

Chrpa, Lukas, McCluskey, Thomas L., Vallati, Mauro, and Vaquero, Tiago

Subjects
Scheduling (Management) -- Conferences, meetings and seminars, Artificial intelligence -- Conferences, meetings and seminars, Artificial intelligence, Business
Abstract

We review the 2016 International Competition on Knowledge Engineering for Planning and Scheduling (ICKEPS), the fifth in a series of competitions started in 2005. The ICKEPS series focuses on promoting [...]

Published
2017

131. Preface

Author

De Benedictis Riccardo, Maratea, Marco, Micheli, Andrea, Scala, Enrico, Serina, Ivan, Vallati, Mauro, and Umbrico, Alessandro

Published
2021

134. What Role Can Process Mining Play in Recurrent Clinical Guidelines Issues? A Position Paper

Author

Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Gatta, Roberto, Vallati, Mauro, Fernández Llatas, Carlos, Martinez-Millana, Antonio, Orini, Stefania, Sacchi, Luccia, Lenkowicz, Jacopo, Marcos, Mar, Munoz-Gama, Jorge, Cuendet, Michel A., de Bari, Berardino, Marco-Ruiz, Luis, Stefanini, Alessandro, Valero Ramon, Zoe, Michielin, Olivier, Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica, Gatta, Roberto, Vallati, Mauro, Fernández Llatas, Carlos, Martinez-Millana, Antonio, Orini, Stefania, Sacchi, Luccia, Lenkowicz, Jacopo, Marcos, Mar, Munoz-Gama, Jorge, Cuendet, Michel A., de Bari, Berardino, Marco-Ruiz, Luis, Stefanini, Alessandro, Valero Ramon, Zoe, and Michielin, Olivier

Abstract

[EN] In the age of Evidence-Based Medicine, Clinical Guidelines (CGs) are recognized to be an indispensable tool to support physicians in their daily clinical practice. Medical Informatics is expected to play a relevant role in facilitating diffusion and adoption of CGs. However, the past pioneering approaches, often fragmented in many disciplines, did not lead to solutions that are actually exploited in hospitals. Process Mining for Healthcare (PM4HC) is an emerging discipline gaining the interest of healthcare experts, and seems able to deal with many important issues in representing CGs. In this position paper, we briefly describe the story and the state-of-the-art of CGs, and the efforts and results of the past approaches of medical informatics. Then, we describe PM4HC, and we answer questions like how can PM4HC cope with this challenge? Which role does PM4HC play and which rules should be employed for the PM4HC scientific community?

Published
2020

139. Summary report of the first international competition on computational models of argumentation

Author

Thimm, Matthias, Villata, Serena, Cerutti, Federico, Oren, Nir, Strass, Hannes, and Vallati, Mauro

Subjects
Debates -- Models, Artificial intelligence -- Research, Engineering research, Computer simulation -- Research, Artificial intelligence, Business
Abstract

We review the First International Competition on Computational Models of Argumentation (ICCMA'15). The competition evaluated submitted solvers' performance on four different computational tasks related to solving abstract argumentation frameworks. Each [...]

Published
2016

146. Preface

Author

Eiter, Thomas, primary, Maratea, Marco, additional, and Vallati, Mauro, additional

Published
2020
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147. What Role Can Process Mining Play in Recurrent Clinical Guidelines Issues? A Position Paper

Author

Gatta, Roberto, primary, Vallati, Mauro, additional, Fernandez-Llatas, Carlos, additional, Martinez-Millana, Antonio, additional, Orini, Stefania, additional, Sacchi, Lucia, additional, Lenkowicz, Jacopo, additional, Marcos, Mar, additional, Munoz-Gama, Jorge, additional, Cuendet, Michel A., additional, de Bari, Berardino, additional, Marco-Ruiz, Luis, additional, Stefanini, Alessandro, additional, Valero-Ramon, Zoe, additional, Michielin, Olivier, additional, Lapinskas, Tomas, additional, Montvila, Antanas, additional, Martin, Niels, additional, Tavazzi, Erica, additional, and Castellano, Maurizio, additional

Published
2020
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150. What You Always Wanted to Know about the Deterministic Part of IPC 2014 (But Were too Afraid to Ask)

Author

Vallati, Mauro, Chrpa, Lukáš, and McCluskey, T.L.

Subjects
QA75
Abstract

The International Planning Competition (IPC) is a prominent event of the AI planning community that has been organised since 1998; it aims at fostering the development and comparison of planning approaches, assessing the state-of-the-art in planning, and identifying new challenging benchmarks. IPC has a strong impact also outside the planning community, by\ud providing a large number of ready-to-use planning engines and testing pioneering applications of planning techniques.\ud This paper focuses on the deterministic part of IPC 2014, and describes format, participants,\ud benchmarks as well as a thorough analysis of the results. Generally, results of the competition indicates some significant progress, but they also highlight issues and challenges that the planning community will have to face in the future.

Published
2018

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