Article contents
Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory?
Published online by Cambridge University Press: 14 May 2013
Abstract
A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.
- Type
- Open Peer Commentary
- Information
- Copyright
- Copyright © Cambridge University Press 2013
References
Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C. & Qin, Y. (2004) An integrated theory of the mind. Psychological Review
111:1036–60.Google Scholar
Anderson, J. R. & Lebiere, C. (2003) The Newell Test for a theory of cognition. Behavioral and Brain Sciences
26:587–640.Google Scholar
Anderson, J. R. & Schooler, L. J. (1991) Reflections of the environment in memory. Psychological Science
2:396–408.Google Scholar
Berg, N. & Gigerenzer, G. (2010) As-if behavioral economics: Neoclassical economics in disguise?
History of Economic Ideas
18:133–66.Google Scholar
Brandstätter, E., Gigerenzer, G. & Hertwig, R. (2006) The priority heuristic: Making choices without trade-offs. Psychological Review
113:409–32.CrossRefGoogle ScholarPubMed
Bröder, A. & Gaissmaier, W. (2007) Sequential processing of cues in memory-based multi-attribute decisions. Psychonomic Bulletin & Review
14:895–900.Google Scholar
Brunswik, E. (1964) Scope and aspects of the cognitive problem. In: Contemporary approaches to cognition, ed. Bruner, J. S., Brunswik, E., Festinger, L., Heider, F., Muenzinger, K. F., Osgood, C. E. & Rapaport, D., pp. 5–31. Harvard University Press.Google Scholar
Dougherty, M. R. P., Gettys, C. F. & Ogden, E. E. (1999) Minerva-DM: A memory processes model for judgments of likelihood. Psychological Review
106:180–209.CrossRefGoogle Scholar
Gigerenzer, G. (1996) On narrow norms and vague heuristics: A reply to Kahneman and Tversky. Psychological Review
103:592–96.Google Scholar
Gigerenzer, G., Hoffrage, U. & Kleinbölting, H. (1991) Probabilistic mental models: A Brunswikian theory of confidence. Psychological Review
98:506–28.Google Scholar
Gigerenzer, G. & Selten, R., ed. (2001) Bounded rationality: The adaptive toolbox. MIT Press.Google Scholar
Griffiths, T. L., Kemp, C. & Tenenbaum, J. B. (2008) Bayesian models of cognition. In: Cambridge handbook of computational cognitive modeling, ed. Sun, R., pp. 59–100. Cambridge University Press.Google Scholar
Hertwig, R., Hoffrage, U. & the ABC Research Group (2013) Simple heuristics in a social world. Oxford University Press.Google Scholar
Hertwig, R., Hoffrage, U. & Martignon, L. (1999) Quick estimation: Letting the environment do the work. In: Simple heuristics that make us smart, Gigerenzer, G., Todd, P. M. & the ABC Research Group, pp. 209–34. Oxford University Press.Google Scholar
Johnson, E.J., Schulte-Mecklenbeck, M. & Willemsen, M. (2008) Process models deserve process data: Comment on Brandstätter, Gigerenzer & Hertwig (2006). Psychological Review
115:263–72.Google Scholar
Kahneman, D., Slovic, P. & Tversky, A. (1982) Judgment under uncertainty: Heuristics and biases. Cambridge University Press.Google Scholar
Marewski, J. N. & Mehlhorn, K. (2011) Using the ACT-R architecture to specify 39 quantitative process models of decision making. Judgment and Decision Making
6(6):439–519.Google Scholar
Marewski, J. N., Pohl, R. F. & Vitouch, O. (2010) Recognition-based judgments and decisions: Introduction to the special issue (Vol. 1). Judgment and Decision Making
5:207–15.Google Scholar
Marewski, J. N. & Schooler, L. J. (2011) Cognitive niches: An ecological model of strategy selection. Psychological Review
118(3):393–437.Google Scholar
Nellen, S. (2003) The use of the “take-the-best” heuristic under different conditions, modelled with ACT-R. In: Proceedings of the fifth international conference on cognitive modelling, ed. Detje, F., Dörner, D. & Schaub, H., pp. 171–76. Universitätsverlag Bamberg.Google Scholar
Oaksford, M. & Chater, N. (1998) Rational models of cognition. Oxford University Press.Google Scholar
Pachur, T., Hertwig, R. & Rieskamp, J. (2013) The mind as an intuitive pollster: Frugal search in social spaces. In: Simple heuristics in a social world, ed. Hertwig, R., Hoffrage, U. & the ABC Research Group, pp. 261–91. Oxford University Press.Google Scholar
Reisen, N., Hoffrage, U. & Mast, F. W. (2008) Identifying decision strategies in a consumer choice situation. Judgment and Decision Making
3:641–58.Google Scholar
Schooler, L. J. & Hertwig, R. (2005) How forgetting aids heuristic inference. Psychological Review
112(3):610–28.Google Scholar
Simon, H. A. (1956) Rational choice and the structure of the environment. Psychological Review
63:129–38.Google Scholar
Sloman, S. A. (1996) The empirical case for two systems of reasoning. Psychological Bulletin
119:3–22.Google Scholar
Todd, P. M., Gigerenzer, G. & the ABC Research Group (2012) Ecological rationality: Intelligence in the world. Oxford University Press.Google Scholar
Volz, K. G., Schooler, L. J. & von Cramon, D. Y. (2010) It just felt right: The neural correlates of the fluency heuristic. Consciousness and Cognition
19:829–37.Google Scholar
A correction has been issued for this article:
- 1
- Cited by
Linked content
Please note a has been issued for this article.
Target article
Can quantum probability provide a new direction for cognitive modeling?
Related commentaries (34)
A quantum of truth? Querying the alternative benchmark for human cognition
At home in the quantum world
Beyond quantum probability: Another formalism shared by quantum physics and psychology
Can quantum probability help analyze the behavior of functional brain networks?
Cognition in Hilbert space
Cognitive architectures combine formal and heuristic approaches
Cold and hot cognition: Quantum probability theory and realistic psychological modeling
Disentangling the order effect from the context effect: Analogies, homologies, and quantum probability
Does quantum uncertainty have a place in everyday applied statistics?
Grounding quantum probability in psychological mechanism
If quantum probability = classical probability + bounded cognition; is this good, bad, or unnecessary?
Is quantum probability rational?
Limitations of the Dirac formalism as a descriptive framework for cognition
On the quantum principles of cognitive learning
Physics envy: Trying to fit a square peg into a round hole
Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory?
Quantum mathematical cognition requires quantum brain biology: The “Orch OR” theory
Quantum modeling of common sense
Quantum models of cognition as Orwellian newspeak
Quantum probability and cognitive modeling: Some cautions and a promising direction in modeling physics learning
Quantum probability and comparative cognition
Quantum probability and conceptual combination in conjunctions
Quantum probability, choice in large worlds, and the statistical structure of reality
Quantum probability, intuition, and human rationality
Quantum structure and human thought
Realistic neurons can compute the operations needed by quantum probability theory and other vector symbolic architectures
Signal detection theory in Hilbert space
The (virtual) conceptual necessity of quantum probabilities in cognitive psychology
The cognitive economy: The probabilistic turn in psychology and human cognition
The implicit possibility of dualism in quantum probabilistic cognitive modeling
Uncertainty about the value of quantum probability for cognitive modeling
What are the mechanics of quantum cognition?
What's the predicted outcome? Explanatory and predictive properties of the quantum probability framework
Why quantum probability does not explain the conjunction fallacy
Author response
Quantum principles in psychology: The debate, the evidence, and the future