Zobrazeno 1 - 10
of 232
pro vyhledávání: '"Iocchi, Luca"'
One major limitation to the applicability of Reinforcement Learning (RL) to many practical domains is the large number of samples required to learn an optimal policy. To address this problem and improve learning efficiency, we consider a linear hiera
Externí odkaz:
http://arxiv.org/abs/2303.00516
Autor:
Crowley, James L., Coutaz, Joëlle L, Grosinger, Jasmin, Vázquez-Salceda, Javier, Angulo, Cecilio, Sanfeliu, Alberto, Iocchi, Luca, Cohn, Anthony G.
Publikováno v:
IEEE Pervasive Computing, 2022
We propose a hierarchical framework for collaborative intelligent systems. This framework organizes research challenges based on the nature of the collaborative activity and the information that must be shared, with each level building on capabilitie
Externí odkaz:
http://arxiv.org/abs/2212.08659
Autor:
Serafini, Luciano, Barbosa, Raul, Grosinger, Jasmin, Iocchi, Luca, Napoli, Christian, Rinzivillo, Salvatore, Robin, Jacques, Saffiotti, Alessandro, Scantamburlo, Teresa, Schueller, Peter, Traverso, Paolo, Vazquez-Salceda, Javier
The burgeoning of AI has prompted recommendations that AI techniques should be "human-centered". However, there is no clear definition of what is meant by Human Centered Artificial Intelligence, or for short, HCAI. This paper aims to improve this sit
Externí odkaz:
http://arxiv.org/abs/2112.14480
Autor:
Brigato, Lorenzo, Iocchi, Luca
Deep neural networks represent the gold standard for image classification. However, they usually need large amounts of data to reach superior performance. In this work, we focus on image classification problems with a few labeled examples per class a
Externí odkaz:
http://arxiv.org/abs/2111.14493
Learning from limited amounts of data is the hallmark of intelligence, requiring strong generalization and abstraction skills. In a machine learning context, data-efficient methods are of high practical importance since data collection and annotation
Externí odkaz:
http://arxiv.org/abs/2109.13561
Data-efficient image classification using deep neural networks in settings, where only small amounts of labeled data are available, has been an active research area in the recent past. However, an objective comparison between published methods is dif
Externí odkaz:
http://arxiv.org/abs/2108.13122
Il progetto Lab2Go per la diffusione della pratica laboratoriale nelle Scuole Secondarie di II grado
Autor:
Andreotti, Mirco, Astone, Pia, Campana, Donatella, Cartoni, Antonella, Casaburo, Fausto, Cavanna, Francesca, Cibinetto, Gianluigi, Cort, Antonella Dalla, De Bonis, Giulia, Della Seta, Marta, Di Mauro, Francesca, Di Sciascio, Giuseppe, Faccini, Riccardo, Favino, Federica, Iocchi, Luca, Lissia, Marcello, Morganti, Giulia, Mancini, Mauro, Organtini, Giovanni, Pennazio, Francesco, Piacentini, Francesco, Piras, Alina, Ragosta, Maria, Roberti, Lorenzo, Rossi, Anna Rita, Sadori, Laura, Tehrani, Francesco Safai
Even if laboratory practice is essential for all scientific branches of knowledge, it is often neglected at High School, due to lack of time and/or resources. To establish a closer contact between school and experimental sciences, the University Sapi
Externí odkaz:
http://arxiv.org/abs/2106.08308
This paper focuses on the emergence of communication to support cooperation in environments modeled as social deduction games (SDG), that are games where players communicate freely to deduce each others' hidden intentions. We first state the problem
Externí odkaz:
http://arxiv.org/abs/2106.05018
Publikováno v:
2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
We design a multi-purpose environment for autonomous UAVs offering different communication services in a variety of application contexts (e.g., wireless mobile connectivity services, edge computing, data gathering). We develop the environment, based
Externí odkaz:
http://arxiv.org/abs/2105.05094
Autor:
Hart, Justin W., DePalma, Nick, Freedman, Richard G., Iocchi, Luca, Leonetti, Matteo, Lohan, Katrin, Mead, Ross, Senft, Emmanuel, Sinapov, Jivko, Topp, Elin A., Williams, Tom
The past few years have seen rapid progress in the development of service robots. Universities and companies alike have launched major research efforts toward the deployment of ambitious systems designed to aid human operators performing a variety of
Externí odkaz:
http://arxiv.org/abs/1909.04812