Connectionism and LOT

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3) Network learning can be slow Many connectionist networks need a large amount of explicit feedback to learn. Others, e.g. selforganizing maps, use unsupervised learning : http://www.willamette.edu/~gorr/classes/cs449/Unsupervised/SOM.html The brain often seems to learn a new concept or pattern in one shot. One-shot learning is especially easy when information is gathered through language. Example: think of teaching an intelligent chimp vs. a five-year-old child, to push the red button for food.
Another weakness of Connectionism Systematicity and productivity: very difficult (impossible) to implement in connectionist architecture. Connectionist responses: 1) Deny systematicity and productivity of the mind: Is human thinking really systematic/productive Do animals think systematically/productively 2) Maintain the ability of connectionist nets to generate systematicity and productivity
Page 1 and 2: Connectionism & Connectionism and L
Page 3 and 4: Types of Connectionist Representati
Page 5 and 6: 2) Distributed representations. E.g
Page 7 and 8: 3) No representation. More controve
Page 9 and 10: LOTH approach: I am thirsty. There
Page 11 and 12: Connectionism makes eliminativism p
Page 13 and 14: Advantages of Connectionism 1) Biol
Page 15 and 16: 3) Performance of connectionist net
Page 17 and 18: 4) Connectionism provides a natural
Page 19 and 20: 1) Biological plausibility Networks
Page 21: 2) The 100 step argument Problem: w
Page 25 and 26: 1) Connectionism implements LOT Con
Page 27 and 28: 3) Hybrid theory Some mental proces
Page 29 and 30: Rule composing the implement and ha
Page 31 and 32: Connectionism and Modularity Connec

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