Quantum models of cognition and decision:
Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2012
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UBG01 URL des Erstveröffentlichers |
| Zusammenfassung: | Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modeling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum entanglement', allows cognitive phenomena to be modeled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light. Introducing the basic principles in an easy-to-follow way, this book does not assume a physics background or a quantum brain and comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xiv, 407 pages) |
| ISBN: | 9780511997716 |
| DOI: | 10.1017/CBO9780511997716 |
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| 505 | 8 | |a Machine generated contents note: 1. Why use quantum theory for cognition and decision? Some compelling reasons; 2. What is quantum theory? An elementary introduction; 3. What can quantum theory predict? Predicting question order effects on attitudes; 4. How to apply quantum theory? Accounting for human probability judgment errors; 5. Quantum inspired models of concept combination; 6. An application of quantum theory to conjoint memory recognition; 7. Quantum-like models of human semantic space; 8. What about quantum dynamics? More advanced principles; 9. What is the quantum advantage? Applications to decision making; 10. How to model human information processing using quantum information theory; 11. Can quantum systems learn? Quantum updating; 12. What are the future prospects for quantum cognition and decision? | |
| 520 | |a Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modeling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum entanglement', allows cognitive phenomena to be modeled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light. Introducing the basic principles in an easy-to-follow way, this book does not assume a physics background or a quantum brain and comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision | ||
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Datensatz im Suchindex
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| author | Busemeyer, Jerome R. |
| author_facet | Busemeyer, Jerome R. |
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| author_sort | Busemeyer, Jerome R. |
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| bvnumber | BV043924728 |
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| contents | Machine generated contents note: 1. Why use quantum theory for cognition and decision? Some compelling reasons; 2. What is quantum theory? An elementary introduction; 3. What can quantum theory predict? Predicting question order effects on attitudes; 4. How to apply quantum theory? Accounting for human probability judgment errors; 5. Quantum inspired models of concept combination; 6. An application of quantum theory to conjoint memory recognition; 7. Quantum-like models of human semantic space; 8. What about quantum dynamics? More advanced principles; 9. What is the quantum advantage? Applications to decision making; 10. How to model human information processing using quantum information theory; 11. Can quantum systems learn? Quantum updating; 12. What are the future prospects for quantum cognition and decision? |
| ctrlnum | (ZDB-20-CBO)CR9780511997716 (OCoLC)1073371066 (DE-599)BVBBV043924728 |
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| dewey-ones | 530 - Physics |
| dewey-raw | 530.12 |
| dewey-search | 530.12 |
| dewey-sort | 3530.12 |
| dewey-tens | 530 - Physics |
| discipline | Physik Psychologie |
| doi_str_mv | 10.1017/CBO9780511997716 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:38:44Z |
| institution | BVB |
| isbn | 9780511997716 |
| language | English |
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| spelling | Busemeyer, Jerome R. Verfasser aut Quantum models of cognition and decision Jerome R. Busemeyer, Peter D. Bruza Quantum Models of Cognition & Decision Cambridge Cambridge University Press 2012 1 online resource (xiv, 407 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Machine generated contents note: 1. Why use quantum theory for cognition and decision? Some compelling reasons; 2. What is quantum theory? An elementary introduction; 3. What can quantum theory predict? Predicting question order effects on attitudes; 4. How to apply quantum theory? Accounting for human probability judgment errors; 5. Quantum inspired models of concept combination; 6. An application of quantum theory to conjoint memory recognition; 7. Quantum-like models of human semantic space; 8. What about quantum dynamics? More advanced principles; 9. What is the quantum advantage? Applications to decision making; 10. How to model human information processing using quantum information theory; 11. Can quantum systems learn? Quantum updating; 12. What are the future prospects for quantum cognition and decision? Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modeling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum entanglement', allows cognitive phenomena to be modeled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light. Introducing the basic principles in an easy-to-follow way, this book does not assume a physics background or a quantum brain and comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision Mathematisches Modell Quantentheorie Decision making / Mathematical models Statistical decision Cognition / Mathematical models Quantum theory Quanteninformatik (DE-588)4705961-8 gnd rswk-swf Entscheidungstheorie (DE-588)4138606-1 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Informationsverarbeitung (DE-588)4161678-9 gnd rswk-swf Quantentheorie (DE-588)4047992-4 gnd rswk-swf Kognition (DE-588)4031630-0 gnd rswk-swf Informationsverarbeitung (DE-588)4161678-9 s Mathematisches Modell (DE-588)4114528-8 s Quantentheorie (DE-588)4047992-4 s 1\p DE-604 Kognition (DE-588)4031630-0 s Quanteninformatik (DE-588)4705961-8 s 2\p DE-604 Entscheidungstheorie (DE-588)4138606-1 s 3\p DE-604 Bruza, Peter David 1962- Sonstige oth Erscheint auch als Druckausgabe 978-1-107-01199-1 Erscheint auch als Druckausgabe 978-1-107-41988-9 https://doi.org/10.1017/CBO9780511997716 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 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Busemeyer, Jerome R. Quantum models of cognition and decision Machine generated contents note: 1. Why use quantum theory for cognition and decision? Some compelling reasons; 2. What is quantum theory? An elementary introduction; 3. What can quantum theory predict? Predicting question order effects on attitudes; 4. How to apply quantum theory? Accounting for human probability judgment errors; 5. Quantum inspired models of concept combination; 6. An application of quantum theory to conjoint memory recognition; 7. Quantum-like models of human semantic space; 8. What about quantum dynamics? More advanced principles; 9. What is the quantum advantage? Applications to decision making; 10. How to model human information processing using quantum information theory; 11. Can quantum systems learn? Quantum updating; 12. What are the future prospects for quantum cognition and decision? Mathematisches Modell Quantentheorie Decision making / Mathematical models Statistical decision Cognition / Mathematical models Quantum theory Quanteninformatik (DE-588)4705961-8 gnd Entscheidungstheorie (DE-588)4138606-1 gnd Mathematisches Modell (DE-588)4114528-8 gnd Informationsverarbeitung (DE-588)4161678-9 gnd Quantentheorie (DE-588)4047992-4 gnd Kognition (DE-588)4031630-0 gnd |
| subject_GND | (DE-588)4705961-8 (DE-588)4138606-1 (DE-588)4114528-8 (DE-588)4161678-9 (DE-588)4047992-4 (DE-588)4031630-0 |
| title | Quantum models of cognition and decision |
| title_alt | Quantum Models of Cognition & Decision |
| title_auth | Quantum models of cognition and decision |
| title_exact_search | Quantum models of cognition and decision |
| title_full | Quantum models of cognition and decision Jerome R. Busemeyer, Peter D. Bruza |
| title_fullStr | Quantum models of cognition and decision Jerome R. Busemeyer, Peter D. Bruza |
| title_full_unstemmed | Quantum models of cognition and decision Jerome R. Busemeyer, Peter D. Bruza |
| title_short | Quantum models of cognition and decision |
| title_sort | quantum models of cognition and decision |
| topic | Mathematisches Modell Quantentheorie Decision making / Mathematical models Statistical decision Cognition / Mathematical models Quantum theory Quanteninformatik (DE-588)4705961-8 gnd Entscheidungstheorie (DE-588)4138606-1 gnd Mathematisches Modell (DE-588)4114528-8 gnd Informationsverarbeitung (DE-588)4161678-9 gnd Quantentheorie (DE-588)4047992-4 gnd Kognition (DE-588)4031630-0 gnd |
| topic_facet | Mathematisches Modell Quantentheorie Decision making / Mathematical models Statistical decision Cognition / Mathematical models Quantum theory Quanteninformatik Entscheidungstheorie Informationsverarbeitung Kognition |
| url | https://doi.org/10.1017/CBO9780511997716 |
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