ANN Learning, Attention, and Memory

Vincenzo Manca

doi:10.20944/preprints202406.0757.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 10 June 2024 / Approved: 11 June 2024 / Online: 12 June 2024 (11:07:59 CEST)

The learning equations of an ANN are presented, giving an extremely concise derivation based on the principle of backpropagation through the descendent gradient. Then, a reflection is developed on the dual attention network that applies the learning equations and coordinates subnetworks toward purposeful behaviors. Speculation is made on possible developments of functionalities that could provide additional skills and at the same time shed light on competencies typical of ``natural intelligence".

Artificial Neural Networks; Machine Learning; Artificial Intelligence; Cognitive Systems; Back-propagation

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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ANN Learning, Attention, and Memory

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