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
6 - An application of quantum theory to conjoint memory recognition
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
One of the goals of quantum Cognition and decision is to explain findings that seem paradoxical from a classic probability point of view. This is important to justify the introduction of this new theory. So far we have used the theory to explain paradoxical findings from research on human probability judgments and conceptual combinations. These are both considered higher level cognitive functions that involve more complex reasoning. What about more primitive cognitive functions such as memory recognition? Do paradoxical findings with respect to classic probability theory occur in this basic area of cognition? If so, how can a quantum model help to explain these findings over and above current explanations? This chapter presents a new application of quantum theory to a puzzling phenomenon observed in human memory recognition called the episodic overdistribution (EOD) effect (Brainerd & Reyna, 2008). First we describe the phenomena and explain why it is a puzzle, and then we present a quantum solution to the puzzle and compare it with previous memory recognition models.
Episodic overdistribution effect
In the conjoint–recognition paradigm, participants are rehearsed on a single set T of memory targets (e.g., each member is a short description of an event). After a delay, a recognition test phase occurs, during which they are presented with a series of test probes that consist of trained targets from T, related non-targets from a different set R of distracting events (e.g., each member is a new event that has some meaningful relation to a target event), and an unrelated set U of non-target items (e.g., each member is completely unrelated to the targets).
- Type
- Chapter
- Information
- Quantum Models of Cognition and Decision , pp. 169 - 184Publisher: Cambridge University PressPrint publication year: 2012