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Multilayer perceptrons can compute all relevant functions
TegenArgument
1
#871
The limitations described by Minsky & Papert don't apply to multilayer networks.
Minsky & Papert ignored such networks in part because there were no useful learning procedures for training them. Today, however there are several effective algorithms for training multilayer networks.
David Rumelhart & James McClelland, 1986b.
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Artificial Intelligence »
Artificial Intelligence
Artificial IntelligenceâA collaboratively editable version of Robert Horns brilliant and pioneering debate map Can Computers Think?âexploring 50 years of philosophical argument about the possibility of computer thought.âF1CEB7
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Can computers think? [1] »
Can computers think? [1]
Can computers think? [1]âCan a computational system possess all important elements of human thinking or understanding? âFFB597
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Yes: connectionist networks can think [5a]
Yes: connectionist networks can think [5a]âConnectionist networks can possess all important elements of human thinking or understanding.â59C6EF
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One-layer perceptrons canât compute certain functions »
One-layer perceptrons canât compute certain functions
One-layer perceptrons canât compute certain functionsâE.g. they cant compute: Parityâwhether an odd or even no. of units in the input layer are activeâand Connectednessâwhether all active units in the input layer are connected to all other active units, either directly, or via other active units.âEF597B
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Multilayer perceptrons can compute all relevant functions
Multilayer perceptrons can compute all relevant functionsâThe limitations described by Minsky & Papert dont apply to multilayer networks.âEF597B
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James McClelland »
James McClelland
James McClellandâArguments advanced by James McClelland.âFFFACD
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David Rumelhart »
David Rumelhart
David RumelhartâArguments advanced by David Rumelhart.âFFFACD
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Gemaakt door:
David Price
NodeID:
#871
Node type:
OpposingArgument
Gemaakt op (GMT):
8/14/2006 4:24:00 PM
Laatste bewerking (GMT):
8/14/2006 4:24:00 PM
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