Formal approaches in categorization:
The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorizati...
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| Weitere Verfasser: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2011
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UBG01 Volltext |
| Zusammenfassung: | The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xii, 336 pages) |
| ISBN: | 9780511921322 |
| DOI: | 10.1017/CBO9780511921322 |
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| 505 | 8 | |a Machine generated contents note: 1. Introduction Emmanuel M. Pothos and Andy J. Wills; 2. The generalized context model: an exemplar model of classification Robert M. Nosofsky; 3. Prototype models of categorization: basic formulation, predictions, and limitations John Paul Minda and J. David Smith; 4. COVIS F. Gregory Ashby, Erick J. Paul and W. Todd Maddox; 5. Semantics without categorization Timothy T. Rogers and James L. McClelland; 6. Models of attentional learning John K. Kruschke; 7. An elemental model of associative learning and memory Evan Livesey and Ian McLaren; 8. Nonparametric Bayesian models of categorization Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, Daniel J. Navarro and Joshua B. Tenenbaum; 9. The simplicity model of unsupervised categorization Emmanuel M. Pothos, Nick Chater and Peter Hines; 10. Adaptive clustering models of categorization John V. McDonnell and Todd M. Gureckis; 11. COBWEB models of categorization and probabilistic concept formation Wayne Iba and Pat Langley; 12. The knowledge and resonance (KRES) model of category learning Harlan D. Harris and Bob Rehder; 13. The contribution (and drawbacks) of models to the study of concepts Gregory L. Murphy; 14. Formal models of categorization: insights from cognitive neuroscience Lukas Strnad, Stefano Anzellotti and Alfonso Caramazza; 15. Comments on models and categorization theories: the razor's edge Douglas Medin | |
| 520 | |a The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come | ||
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Datensatz im Suchindex
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| author2 | Pothos, Emmanuel M. 1973- Wills, Andy J. 1972- |
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| contents | Machine generated contents note: 1. Introduction Emmanuel M. Pothos and Andy J. Wills; 2. The generalized context model: an exemplar model of classification Robert M. Nosofsky; 3. Prototype models of categorization: basic formulation, predictions, and limitations John Paul Minda and J. David Smith; 4. COVIS F. Gregory Ashby, Erick J. Paul and W. Todd Maddox; 5. Semantics without categorization Timothy T. Rogers and James L. McClelland; 6. Models of attentional learning John K. Kruschke; 7. An elemental model of associative learning and memory Evan Livesey and Ian McLaren; 8. Nonparametric Bayesian models of categorization Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, Daniel J. Navarro and Joshua B. Tenenbaum; 9. The simplicity model of unsupervised categorization Emmanuel M. Pothos, Nick Chater and Peter Hines; 10. Adaptive clustering models of categorization John V. McDonnell and Todd M. Gureckis; 11. COBWEB models of categorization and probabilistic concept formation Wayne Iba and Pat Langley; 12. The knowledge and resonance (KRES) model of category learning Harlan D. Harris and Bob Rehder; 13. The contribution (and drawbacks) of models to the study of concepts Gregory L. Murphy; 14. Formal models of categorization: insights from cognitive neuroscience Lukas Strnad, Stefano Anzellotti and Alfonso Caramazza; 15. Comments on models and categorization theories: the razor's edge Douglas Medin |
| ctrlnum | (ZDB-20-CBO)CR9780511921322 (OCoLC)891454143 (DE-599)BVBBV043925652 |
| dewey-full | 153.2 |
| dewey-hundreds | 100 - Philosophy & psychology |
| dewey-ones | 153 - Conscious mental processes & intelligence |
| dewey-raw | 153.2 |
| dewey-search | 153.2 |
| dewey-sort | 3153.2 |
| dewey-tens | 150 - Psychology |
| discipline | Psychologie |
| doi_str_mv | 10.1017/CBO9780511921322 |
| format | Electronic eBook |
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| spelling | Formal approaches in categorization Emmanuel M. Pothos, Andy J. Wills, Editors Cambridge Cambridge University Press 2011 1 online resource (xii, 336 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Machine generated contents note: 1. Introduction Emmanuel M. Pothos and Andy J. Wills; 2. The generalized context model: an exemplar model of classification Robert M. Nosofsky; 3. Prototype models of categorization: basic formulation, predictions, and limitations John Paul Minda and J. David Smith; 4. COVIS F. Gregory Ashby, Erick J. Paul and W. Todd Maddox; 5. Semantics without categorization Timothy T. Rogers and James L. McClelland; 6. Models of attentional learning John K. Kruschke; 7. An elemental model of associative learning and memory Evan Livesey and Ian McLaren; 8. Nonparametric Bayesian models of categorization Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, Daniel J. Navarro and Joshua B. Tenenbaum; 9. The simplicity model of unsupervised categorization Emmanuel M. Pothos, Nick Chater and Peter Hines; 10. Adaptive clustering models of categorization John V. McDonnell and Todd M. Gureckis; 11. COBWEB models of categorization and probabilistic concept formation Wayne Iba and Pat Langley; 12. The knowledge and resonance (KRES) model of category learning Harlan D. Harris and Bob Rehder; 13. The contribution (and drawbacks) of models to the study of concepts Gregory L. Murphy; 14. Formal models of categorization: insights from cognitive neuroscience Lukas Strnad, Stefano Anzellotti and Alfonso Caramazza; 15. Comments on models and categorization theories: the razor's edge Douglas Medin The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come Categorization (Psychology) Kategorisierung (DE-588)4163445-7 gnd rswk-swf Psychologie (DE-588)4047704-6 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Kategorisierung (DE-588)4163445-7 s Psychologie (DE-588)4047704-6 s 2\p DE-604 Pothos, Emmanuel M. 1973- edt Wills, Andy J. 1972- edt Erscheint auch als Druckausgabe 978-0-521-14072-0 Erscheint auch als Druckausgabe 978-0-521-19048-0 https://doi.org/10.1017/CBO9780511921322 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Formal approaches in categorization Machine generated contents note: 1. Introduction Emmanuel M. Pothos and Andy J. Wills; 2. The generalized context model: an exemplar model of classification Robert M. Nosofsky; 3. Prototype models of categorization: basic formulation, predictions, and limitations John Paul Minda and J. David Smith; 4. COVIS F. Gregory Ashby, Erick J. Paul and W. Todd Maddox; 5. Semantics without categorization Timothy T. Rogers and James L. McClelland; 6. Models of attentional learning John K. Kruschke; 7. An elemental model of associative learning and memory Evan Livesey and Ian McLaren; 8. Nonparametric Bayesian models of categorization Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, Daniel J. Navarro and Joshua B. Tenenbaum; 9. The simplicity model of unsupervised categorization Emmanuel M. Pothos, Nick Chater and Peter Hines; 10. Adaptive clustering models of categorization John V. McDonnell and Todd M. Gureckis; 11. COBWEB models of categorization and probabilistic concept formation Wayne Iba and Pat Langley; 12. The knowledge and resonance (KRES) model of category learning Harlan D. Harris and Bob Rehder; 13. The contribution (and drawbacks) of models to the study of concepts Gregory L. Murphy; 14. Formal models of categorization: insights from cognitive neuroscience Lukas Strnad, Stefano Anzellotti and Alfonso Caramazza; 15. Comments on models and categorization theories: the razor's edge Douglas Medin Categorization (Psychology) Kategorisierung (DE-588)4163445-7 gnd Psychologie (DE-588)4047704-6 gnd |
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| title | Formal approaches in categorization |
| title_auth | Formal approaches in categorization |
| title_exact_search | Formal approaches in categorization |
| title_full | Formal approaches in categorization Emmanuel M. Pothos, Andy J. Wills, Editors |
| title_fullStr | Formal approaches in categorization Emmanuel M. Pothos, Andy J. Wills, Editors |
| title_full_unstemmed | Formal approaches in categorization Emmanuel M. Pothos, Andy J. Wills, Editors |
| title_short | Formal approaches in categorization |
| title_sort | formal approaches in categorization |
| topic | Categorization (Psychology) Kategorisierung (DE-588)4163445-7 gnd Psychologie (DE-588)4047704-6 gnd |
| topic_facet | Categorization (Psychology) Kategorisierung Psychologie Aufsatzsammlung |
| url | https://doi.org/10.1017/CBO9780511921322 |
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