Notwithstanding the important advances in Artificial Intelligence (AI) and robotics, artificial agents still lack the necessary autonomy and versatility to properly interact with realistic environments. This requires agents to face situations that are unknown at design time, to autonomously discover multiple goals/tasks, and to be endowed with learning processes able to solve multiple tasks incrementally and online.

Intrinsically Motivated Open-Ended Learning in Autonomous Robots

Santucci Vieri Giuliano
Primo
;
Baldassarre Gianluca
2020

Abstract

Notwithstanding the important advances in Artificial Intelligence (AI) and robotics, artificial agents still lack the necessary autonomy and versatility to properly interact with realistic environments. This requires agents to face situations that are unknown at design time, to autonomously discover multiple goals/tasks, and to be endowed with learning processes able to solve multiple tasks incrementally and online.
2020
Istituto di Scienze e Tecnologie della Cognizione - ISTC
intrinsic motivation
open-ended learning
robotics
developmental robotics
curiosity driven learning
File in questo prodotto:
File Dimensione Formato  
SantucciEtAl_FrontiersEditorial.pdf

accesso aperto

Descrizione: Santucci VG, Oudeyer P-Y, Barto A and Baldassarre G (2020) Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots. Front. Neurorobot. 13:115. doi: 10.3389/fnbot.2019.00115
Tipologia: Versione Editoriale (PDF)
Licenza: Creative commons
Dimensione 134.23 kB
Formato Adobe PDF
134.23 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/405069
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 27
  • ???jsp.display-item.citation.isi??? 21
social impact