Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 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 combinations
- 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?
- Appendices
- References
- Index
2 - What is quantum theory? An elementary introduction
Published online by Cambridge University Press: 05 August 2012
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 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 combinations
- 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?
- Appendices
- References
- Index
Summary
What can you learn about quantum theory in one chapter without knowing any physics? A complete presentation of quantum theory requires an entire textbook, but our goal for this chapter is to provide only the essential elements of the theory that we feel are relevant for modelling behavioral phenomena. Just like classical probability theory, quantum theory is based on a small set of axioms used to assign probabilities to events. This chapter is limited to what is called the structural principles of quantum theory, whereas Chapter 8 will set out the dynamic principles. For simplicity, only finite state systems will be described, although quantum theory can also be applied to continuous state systems. Even though this book is limited to finite dimensions, the number of dimensions can be arbitrarily large.
For finite state systems, the structural part of quantum theory is expressed in the formalism of linear algebra (for continuous state systems, it is expressed in the formalism of functional analysis). Consequently, a brief tutorial of linear algebra is presented along with our elementary introduction to quantum theory. Various notations are used to describe linear algebra, depending on the application field. Physicists like to use Dirac notation, invented by one of the founders of quantum theory, Paul Dirac (Dirac, 1958). Although the Dirac notation will be unfamiliar to many cognitive scientists, we will still use it as it is a succinct notation for expressing linear algebra. It helps the reader to see relations that are more difficult to identify using other formalisms.
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- Information
- Quantum Models of Cognition and Decision , pp. 28 - 98Publisher: Cambridge University PressPrint publication year: 2012