Humans and Machines: Nature of Learning and Learning of Nature

Abstract : Old and recent theories stress that any understanding of the processes by which humans can learn requires to fully appreciate the relationships between the " nature of learning " and the " learning of nature. " From a constructivist viewpoint, acquiring knowledge is, like any human activity, dissociable neither from its underlying project nor from the knowing subject. We relate the lessons from philosophy, psychology, didactics and ethics to our work in computational scientific discovery that aims at empowering learning machines with the task of assisting human researchers (Dartnell, Martin, Hagège, & Sallantin, 2008). We conclude with didactical and ethical considerations.
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https://hal.umontpellier.fr/hal-01685928
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  • HAL Id : hal-01685928, version 1

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Hélène Hagège, Christopher Dartnell, Eric Martin, Jean Sallantin. Humans and Machines: Nature of Learning and Learning of Nature. Y. Wang. Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence, IGI Global, pp.71-92, 2010. ⟨hal-01685928⟩

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