Compositionality in rational analysis: Grammar-based induction for concept learning
This chapter provides a range of conceptual and technical insights into how this project can be attempted - and goes some way to suggesting that probabilistic methods need not be viewed as inevitably unable to capture the richness and complexity of world knowledge. It argues that structured represen...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press
2020
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| Online Access: | https://hdl.handle.net/1721.1/124810 |
| _version_ | 1826213306151469056 |
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| author | Goodman, Noah D. Tenenbaum, Joshua B. Griffiths, Thomas L. Feldman, Jacob |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Goodman, Noah D. Tenenbaum, Joshua B. Griffiths, Thomas L. Feldman, Jacob |
| author_sort | Goodman, Noah D. |
| collection | MIT |
| description | This chapter provides a range of conceptual and technical insights into how this project can be attempted - and goes some way to suggesting that probabilistic methods need not be viewed as inevitably unable to capture the richness and complexity of world knowledge. It argues that structured representations, generated by a formal grammar, can be appropriate units over which probabilistic information can be represented and learned. This topic is likely to be one of the main challenges for probabilistic research in cognitive science and artificial intelligence over the coming decades. Keywords: probabilistic research; knowledge; grammar; concept learning; cognitive science; artificial intelligence |
| first_indexed | 2024-09-23T15:46:59Z |
| format | Article |
| id | mit-1721.1/124810 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:46:59Z |
| publishDate | 2020 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | mit-1721.1/1248102022-09-29T16:07:07Z Compositionality in rational analysis: Grammar-based induction for concept learning Goodman, Noah D. Tenenbaum, Joshua B. Griffiths, Thomas L. Feldman, Jacob Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences This chapter provides a range of conceptual and technical insights into how this project can be attempted - and goes some way to suggesting that probabilistic methods need not be viewed as inevitably unable to capture the richness and complexity of world knowledge. It argues that structured representations, generated by a formal grammar, can be appropriate units over which probabilistic information can be represented and learned. This topic is likely to be one of the main challenges for probabilistic research in cognitive science and artificial intelligence over the coming decades. Keywords: probabilistic research; knowledge; grammar; concept learning; cognitive science; artificial intelligence 2020-04-22T18:07:59Z 2020-04-22T18:07:59Z 2008 2019-10-04T14:33:18Z Article http://purl.org/eprint/type/BookItem 9780199216093 https://hdl.handle.net/1721.1/124810 Goodman, Noah D. et al. "Compositionality in rational analysis: Grammar-based induction for concept learning." The Probabilistic Mind: Prospects for Bayesian Cognitive Science, edited by Nick Chater and Mike Oaksford, Oxford University Press, 2008. © 2008 Oxford University Press en http://dx.doi.org/10.1093/acprof:oso/9780199216093.003.0017 The Probabilistic Mind: Prospects for Bayesian Cognitive Science Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Oxford University Press other univ website |
| spellingShingle | Goodman, Noah D. Tenenbaum, Joshua B. Griffiths, Thomas L. Feldman, Jacob Compositionality in rational analysis: Grammar-based induction for concept learning |
| title | Compositionality in rational analysis: Grammar-based induction for concept learning |
| title_full | Compositionality in rational analysis: Grammar-based induction for concept learning |
| title_fullStr | Compositionality in rational analysis: Grammar-based induction for concept learning |
| title_full_unstemmed | Compositionality in rational analysis: Grammar-based induction for concept learning |
| title_short | Compositionality in rational analysis: Grammar-based induction for concept learning |
| title_sort | compositionality in rational analysis grammar based induction for concept learning |
| url | https://hdl.handle.net/1721.1/124810 |
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