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GOAL-Robots

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Goal based Open ended Autonomous Learning Robots

This project aims to develop a new paradigm to build open-ended learning robots called `Goal-based Open-ended Autonomous Learning' (GOAL). GOAL rests upon two key insights. First, to exhibit an autonomous open-ended learning proce... ver más

30/04/2021

CNR

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

CONSIGLIO NAZIONALE DELLE RICERCHE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 7 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-04-30

FETOPEN-RIA-2014-2015: FET-Open research projects Scope:Specific challenge: Supporting a large set of early stage, high risk visionary science and tec...

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Características del participante

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

7 Participantes

CNR

1.28M€ | Lider

ANTERAL

229.36K€ | Participante

UPCité

555.17K€ | Participante

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Duración del proyecto: 59 meses Fecha Inicio: 2016-05-16
Fecha Fin: 2021-04-30

Líder del proyecto

CONSIGLIO NAZIONALE DELLE RICERCHE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto This project aims to develop a new paradigm to build open-ended learning robots called `Goal-based Open-ended Autonomous Learning' (GOAL). GOAL rests upon two key insights. First, to exhibit an autonomous open-ended learning process, robots should be able to self-generate goals, and hence tasks to practice. Second, new learning algorithms can leverage self-generated goals to dramatically accelerate skill learning. The new paradigm will allow robots to acquire a large repertoire of flexible skills in conditions unforeseeable at design time with little human intervention, and then to exploit these skills to efficiently solve new user-defined tasks with no/little additional learning. This innovation will be essential in the design of future service robots addressing pressing societal needs. The project will develop the GOAL paradigm by pursuing three main objectives: (1) advance our understanding of how goals are formed and underlie skill learning in children; (2) develop innovative computational architectures and algorithms supporting (2a) the self-generation of useful goals based on user/task independent mechanisms such as intrinsic motivations, and (2b) the use of such goals to efficiently and autonomously build large repertoires of skills; (3) demonstrate the potential of GOAL with a series of increasingly challenging demonstrators in which robots will autonomously develop complex skills and use them to solve difficult challenges in real-life scenarios. The interdisciplinary project consortium is formed by leading international roboticists, computational modelers, and developmental psychologists working with complementary approaches. This will allow the project to greatly advance our understanding of the fundamental principles of open-ended learning and to produce a breakthrough in the field of autonomous robotics by producing for the first time robots that can autonomously accumulate complex skills and knowledge in a truly open-ended way.

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