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20182023
most citedOptimal Options for Multi-Task Reinforcement Learning Under Time Constraints

3 citations · 4 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.AI2023

A method for the ethical analysis of brain-inspired AI

Michele Farisco, Gianluca Baldassarre, Emilio Cartoni +6

Despite its successes, to date Artificial Intelligence (AI) is still characterized by a number of shortcomings with regards to different application domains and goals. These limita…

cs.AI20191 cited

Intrinsic motivations and open-ended learning

Gianluca Baldassarre

There is a growing interest and literature on intrinsic motivations and open-ended learning in both cognitive robotics and machine learning on one side, and in psychology and neuro…

cs.AI2019

Learning High-Level Planning Symbols from Intrinsically Motivated Experience

Angelo Oddi, Riccardo Rasconi, Emilio Cartoni +3

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 cre…

cs.AI2019

Autonomous Open-Ended Learning of Interdependent Tasks

Vieri Giuliano Santucci, Emilio Cartoni, Bruno Castro da Silva +1

Autonomy is fundamental for artificial agents acting in complex real-world scenarios. The acquisition of many different skills is pivotal to foster versatile autonomous behaviour a…

cs.AI2018

Autonomous discovery of the goal space to learn a parameterized skill

Emilio Cartoni, Gianluca Baldassarre

A parameterized skill is a mapping from multiple goals/task parameters to the policy parameters to accomplish them. Existing works in the literature show how a parameterized skill…