Connectionist symbol processing / (Record no. 72939)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03015nam a2200541 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 6267281 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220712204618.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 151223s1991 maua ob 001 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780262256360 |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | paperback |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | |
| 082 00 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 245 00 - TITLE STATEMENT | |
| Title | Connectionist symbol processing / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st MIT Press ed. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 PDF (262 pages) : |
| 490 1# - SERIES STATEMENT | |
| Series statement | Special issues of <i>artificial intelligence</i> |
| 500 ## - GENERAL NOTE | |
| Remark 1 | "A Bradford book." |
| 500 ## - GENERAL NOTE | |
| Remark 1 | "Reprinted from Artificial intelligence, an international journal, volume 46, numbers 1-2, 1990"--T.p. verso. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The six contributions in Connectionist Symbol Processing address the current tension within the artificial intelligence community between advocates of powerful symbolic representations that lack efficient learning procedures and advocates of relatively simple learning procedures that lack the ability to represent complex structures effectively. The authors seek to extend the representational power of connectionist networks without abandoning the automatic learning that makes these networks interesting.Aware of the huge gap that needs to be bridged, the authors intend their contributions to be viewed as exploratory steps in the direction of greater representational power for neural networks. If successful, this research could make it possible to combine robust general purpose learning procedures and inherent representations of artificial intelligence -- a synthesis that could lead to new insights into both representation and learning. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Hinton, Geoffrey E. |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267281 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cambridge, Massachusetts : |
| -- | MIT Press, |
| -- | 1991. |
| 264 #2 - | |
| -- | [Piscataqay, New Jersey] : |
| -- | IEEE Xplore, |
| -- | [1991] |
| 336 ## - | |
| -- | text |
| -- | rdacontent |
| 337 ## - | |
| -- | electronic |
| -- | isbdmedia |
| 338 ## - | |
| -- | online resource |
| -- | rdacarrier |
| 588 ## - | |
| -- | Description based on PDF viewed 12/23/2015. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Connection machines. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Neural networks (Computer science) |
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