Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Rasconi, Riccardo"'
Recently, AI systems have made remarkable progress in various tasks. Deep Reinforcement Learning(DRL) is an effective tool for agents to learn policies in low-level state spaces to solve highly complex tasks. Researchers have introduced Intrinsic Mot
Externí odkaz:
http://arxiv.org/abs/2409.11756
Autor:
Sartor, Gabriele, Zollo, Davide, Mayer, Marta Cialdea, Oddi, Angelo, Rasconi, Riccardo, Santucci, Vieri Giuliano
In this work we present an empirical study where we demonstrate the possibility of developing an artificial agent that is capable to autonomously explore an experimental scenario. During the exploration, the agent is able to discover and learn intere
Externí odkaz:
http://arxiv.org/abs/2206.01815
Publikováno v:
In Applied Soft Computing Journal September 2023 144
Autor:
Oddi, Angelo, Rasconi, Riccardo, Cartoni, Emilio, Sartor, Gabriele, Baldassarre, Gianluca, Santucci, Vieri Giuliano
In symbolic planning systems, the knowledge on the domain is commonly provided by an expert. Recently, an automatic abstraction procedure has been proposed in the literature to create a Planning Domain Definition Language (PDDL) representation, which
Externí odkaz:
http://arxiv.org/abs/1907.08313
Publikováno v:
In Engineering Applications of Artificial Intelligence October 2022 115
Publikováno v:
In Swarm and Evolutionary Computation March 2022 69
Akademický článek
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Publikováno v:
In Computers and Operations Research August 2015 60:37-54
Autor:
Oddi, Angelo1 (AUTHOR) angelo.oddi@istc.cnr.it, Rasconi, Riccardo1 (AUTHOR) riccardo.rasconi@istc.cnr.it, Eiter, Thomas (AUTHOR), Maratea, Marco (AUTHOR), Vallati, Mauro (AUTHOR)
Publikováno v:
Fundamenta Informaticae. 2020, Vol. 174 Issue 3/4, p259-281. 23p.
Autor:
Oddi, Angelo1 angelo.oddi@istc.cnr.it, Rasconi, Riccardo1
Publikováno v:
Intelligenza Artificiale. 2016, Vol. 10 Issue 2, p147-160. 14p.