REAL-X -- Robot open-Ended Autonomous Learning Architectures: Achieving Truly End-to-End Sensorimotor Autonomous Learning Systems

1 code implementation • 27 Nov 2020 • Emilio Cartoni, Davide Montella, Jochen Triesch, Gianluca Baldassarre

The first contribution of this work is to study the challenges posed by the previously proposed benchmark `REAL competition' aiming to foster the development of truly open-ended learning robot architectures.

Autonomous learning of multiple, context-dependent tasks

no code implementations • 27 Nov 2020 • Vieri Giuliano Santucci, Davide Montella, Bruno Castro da Silva, Gianluca Baldassarre

These situations pose two challenges: (a) to recognise the different contexts that need different policies; (b) quickly learn the policies to accomplish the same tasks in the new discovered contexts.

Transfer Learning