Reflective Interpretive Frameworks • Incident 2

Re: Terence TaoModular Arithmetic Challenge

  • Can a neural network learn to do modular multiplication efficiently?

Incidental Reflection 1

There are alternative models of neural networks which do not depend on threshold neurons and endlessly fiddling with weights.

Incidental Reflection 2

The series of three blog posts linked below present a case study comparing two ways of handling a classic example from the Parallel Distributed Processing paradigm, namely, the “Jets and Sharks” database problem, first taking up the original treatment by McClelland and Rumelhart and then proceeding according to a program I developed for propositional logic modeling.  The latter method makes use of ideas from Grossberg’s competition‑cooperation and winner‑take‑all dynamics, but is purely propositional‑logic based, involving no extraneous weights.

  • Theme One Program • Jets and Sharks • (1)(2)(3)

Resources

cc: Academia.eduCyberneticsLaws of FormMathstodon
cc: Research GateStructural ModelingSystems ScienceSyscoi

This entry was posted in Arithmetization, C.S. Peirce, Gödel Numbers, Higher Order Sign Relations, Inquiry Driven Systems, Inquiry Into Inquiry, Logic, Mathematics, Quotation, Recursion, Reflection, Reflective Interpretive Frameworks, Semiotics, Sign Relations, Triadic Relations, Use and Mention, Visualization and tagged , , , , , , , , , , , , , , , , . Bookmark the permalink.

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