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Gradland: On Phenomenal Experience, Differentiated Across Many Dimensions

Balduzzi, David
arXiv (All) · Papers
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artificial-intelligenceneural-and-evolutionary-computing
This paper investigates the hypothesis that the first-order structure of physical interactions, i.e. gradients or Jacobians, characterizes the structure of phenomenal experience. It does so in an idealized world inhabited by neural networks, Gradland, where the physics are known and the functions ar
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