Economics Dictionary of ArgumentsHome
| |||
|
| |||
| 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._____________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._____________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 |
||
> Counter arguments against Pauen
> Counter arguments in relation to Connectionism
