The effects of implementing phenomenology in a deep neural network.

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Title

The effects of implementing phenomenology in a deep neural network.

Content partner

The University of Auckland Library

Collection

ResearchSpace@Auckland

Description

There have been several recent attempts at using Artificial Intelligence systems to model aspects of consciousness (Gamez, 2008; Reggia, 2013). Deep Neural Networks have been given additional functionality in the present attempt, allowing them to emulate phenological aspects of consciousness by self-generating information representing multi-modal inputs as either sounds or images. We added these functions to determine whether knowledge of the input's modality aids the networks' learning. In s...

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Format

Research paper

Research format

Journal article

Date created

2021-06-08

Creator

Bensemann, Joshua / Witbrock, Michael

URL

https://hdl.handle.net/2292/59376

Related subjects

Hebbian learning / Neural network / Synthetic phenomenology / Neurosciences / 1.2 Psychological and socioeconomic processes / Mental health / Science & Technology / Multidisciplinary Sciences / Science & Technology - Other Topics / CONSCIOUSNESS

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