Prediction: An Algorithmic Principle Meeting Neuroscience and Machine Learning Halfway

Younes Bouhadjar, Caterina Moruzzi, Melika Payvand

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In this paper, we support the relevance of the collaboration and mutual inspiration between research in Artificial Intelligence and neuroscience to create truly intelligent and efficient systems. In contrast to the traditional top-down and bottom-up strategies designed to study and emulate the brain, we propose an alternative approach where these two strategies are met halfway, defining a set of algorithmic principles. We present prediction as a core algorithmic principle and advocate for applying the same approach to identify other neural principles which can constitute core mechanisms of new Machine Learning frameworks.
Original languageEnglish
Title of host publicationProceedings of the 3rd Human-Like Computing Workshop (HLC 2022) co-located with the 2nd International Joint Conference on Learning and Reasoning (IJCLR 2022)
EditorsAlan Bundy, Denis Mareschal
PublisherCEUR Workshop Proceedings
Pages46-52
Number of pages7
Publication statusPublished - 28 Sept 2022

Publication series

NameCEUR workshop proceedings
ISSN (Electronic)1613-0073

Keywords / Materials (for Non-textual outputs)

  • Prediction
  • Neuroscience
  • Reasoning
  • Algorithmic principles
  • Computation
  • Bottom-up
  • Top-down

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