Morphological computation and learning to learn in natural intelligent systems and AI
Paper in proceeding, 2021

At present, artificial intelligence in the form of machine learning is making impressive progress, especially the field of deep learning (DL) [1]. Deep learning algorithms have been inspired from the beginning by nature, specifically by the human brain, in spite of our incomplete knowledge about its brain function. Learning from nature is a two-way process as discussed in [2][3][4], computing is learning from neuroscience, while neuroscience is quickly adopting information processing models. The question is, what can the inspiration from computational nature at this stage of the development contribute to deep learning and how much models and experiments in machine learning can motivate, justify and lead research in neuroscience and cognitive science and to practical applications of artificial intelligence.


Gordana Dodig Crnkovic

Chalmers, Computer Science and Engineering (Chalmers), Interaction design

Mälardalens högskola

AISB Convention 2021: Communication and Conversations

9781713829423 (ISBN)

AISB Convention 2021: Communication and Conversations
Virtual, Online, ,

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Language Technology (Computational Linguistics)


Information Science

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1/3/2024 9