Philosophy Dictionary of Arguments

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Connectionism: Connectionism is the theory of neural networks as an explanation for mind states and learning. See also Neural networks, Networks, Learning, Artificial Intelligence, Artificial Neural Networks.
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Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments.

 
Author Concept Summary/Quotes Sources

Michael Pauen on Connectionism - Dictionary of Arguments

Pauen I 148
Neural networks/Fodor: work quite unlike computer (and computation) - namely associative.
>Computational model
, >Computation, >Neural networks, >Association.
I 152
Learning: here neural networks are superior to computers where program and data are separated.
>Learning, >Machine Learning, >Artificial Intelligence.
I 155
VsNeural networks: they cannot explain the systematic nature and productivity of thinking.
>Thinking, >Consciousness, >Knowledge.
I 153
Artificial neural networks/Pauen: Back Programming: retroactive effect of information.
Punch line: weight of compounds can be differentiated - learning: here the intervention of the experimenter is needed - large fault tolerance - strength: pattern recognition.
Cf. >Backtracking/Norvig.

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Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments
The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.

Pauen I
M. Pauen
Grundprobleme der Philosophie des Geistes Frankfurt 2001


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Ed. Martin Schulz, access date 2024-04-20
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