|Theory of neural networks as an explanation for mind states.:_____________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. |
|Pauen I 148
Neural networks/Fodor: work quite unlike computer (and computation) - namely associative:
Learning: here neural networks are superior to computers where program and data are separated:
VsNeural networks: they cannot explain the systematic nature and productivity of thinking -
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. ((s) Cf. >Backtracking/Norvig.)_____________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. The note [Author1]Vs[Author2] or [Author]Vs[term] is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.
Grundprobleme der Philosophie des Geistes Frankfurt 2001