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Quantum decision corrections for the neuroeconomics of irrational movement control and goal attainment

Published online by Cambridge University Press:  30 September 2021

Kevin B. Clark Open the ORCID record for Kevin B. Clark [Opens in a new window]
Kevin B. Clark*
Affiliation:
Felidae Conservation Fund, Mill Valley, CA94941, USA Campus and Domain Champions, Extreme Science and Engineering Discovery Environment (XSEDE), National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL61801, USA Expert Network, Penn Center for Innovation, University of Pennsylvania, Philadelphia, PA19104, USA Network for Life Detection (NfoLD), NASA Astrobiology Program, NASA Ames Research Center, Mountain View, CA94035, USA SETI Institute, Mountain View, CA94043, USA Peace Innovation Institute, The Hague 2511, Netherlands and Peace Innovation Institute, Stanford University, Palo Alto, CA94305, USA Shared Interest Group for Natural and Artificial Intelligence (sigNAI), Max Planck Alumni Association, 14057Berlin, Germany Biometrics and Nanotechnology Councils, Institute for Electrical and Electronics Engineers (IEEE), New York, NY 10016-5997, USA. [email protected]; www.linkedin.com/pub/kevin-clark/58/67/19a
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Abstract

Quantum decision theory corrects categorical and propositional logic pathologies common to classic statistical goal-oriented reasoning, such as rational neuroeconomics-based optimal foraging. Within this ecosalient framework, motivation, perception, learning, deliberation, brain computation, and conjunctive risk-order errors may be understood for subjective utility judgments underlying either rational or irrational canonical decisions-actions used to choose, procure, and consume rewarding nutrition with variable fitness.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 44 , 2021 , e127
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Aerts, D. (2009). Quantum structure in cognition. Journal of Mathematical Psychology, 53, 314–348.CrossRefGoogle Scholar
Aerts, D., & Aerts, S. (1995). Applications of quantum statistics in psychological studies of decision processes. Foundations of Science, 1, 85–97.CrossRefGoogle Scholar
Allais, M. (1953). Le comportement de l'homme rationnel devant le risque, critique des postulats et axiomes de l'eÂcole Ame ricaine. Econometrica, 21, 503–546.CrossRefGoogle Scholar
Ashtiani, M., & Azgomi, M. A. (2015). A survey of quantum-like approaches to decision making and cognition. Mathematical Social Sciences, 75, 49–80.CrossRefGoogle Scholar
Atmanspacher, H., & Römer, H. (2012). Order effects in sequential measurements of noncommuting psychological observables. Journal of Mathematical Psychology, 56, 274–280.CrossRefGoogle Scholar
Bautista, L. M., Tinbergen, J., & Kacelnik, A. (2001). To walk or to fly? How birds choose among foraging modes. Proceedings of the National Academy of Sciences USA, 98, 1089–1094.CrossRefGoogle ScholarPubMed
Beck, N. (2016). The spontaneous market order and evolution. Studies on the History and Philosophy of Biological and Biomedical Sciences, 58, 49–55.CrossRefGoogle ScholarPubMed
Busemeyer, J. R., & Bruza, P. (2011). Quantum models of cognition and decision making. Cambridge: Cambridge University Press. ISBN-13 978–1107419889.Google Scholar
Busemeyer, J. R., Pothos, E., Franco, R., & Trueblood, J. S. (2011). A quantum theoretical explanation for probability judgment “errors.” Psychological Reviews, 118, 193–218.CrossRefGoogle Scholar
Chater, N. (2015). Can cognitive science create a cognitive economics? Cognition, 35, 52–55.CrossRefGoogle Scholar
Clark, K. B. (2011). Live soft-matter quantum computing. In Salander, E. C. (Ed.), Computer search algorithms (pp. 1–24). Nova Science Publishers, Inc. ISBN 978-1-61122-527-3.Google Scholar
Clark, K. B. (2012a). A statistical mechanics definition of insight. In Floares, A. G. (Ed.), Computational intelligence (pp. 139–162). Nova Science Publishers, Inc. ISBN 978-1-62081-901-2.Google Scholar
Clark, K. B. (2012b). Bioreaction quantum computing without quantum diffusion. NeuroQuantology, 10(4), 646–654.CrossRefGoogle Scholar
Clark, K. B. (2014a). Evolution of affective and linguistic disambiguation under social eavesdropping pressures. Behavioral and Brain Sciences, 37(6), 551–552.CrossRefGoogle Scholar
Clark, K. B. (2014b). Basis for a neuronal version of Grover's quantum algorithm. Frontiers in Molecular Neuroscience, 7, 29.CrossRefGoogle Scholar
Clark, K. B. (2015). Insight and analysis problem solving in microbes to machines. Progress in Biophysics and Molecular Biology, 119, 183–193.CrossRefGoogle ScholarPubMed
Clark, K. B. (2017). Cognitive completeness of quantum teleportation and superdense coding in neuronal response regulation and plasticity. Proceedings of the Royal Society B: Biological Sciences. eLetter: https://royalsocietypublishing.org/doi/suppl/10.1098/rspb.2013.3056.Google Scholar
Clark, K. B. (2018). Possible origins of consciousness in simple control over “involuntary” neuroimmunological action. Consciousness and Cognition, 61, 76–78.CrossRefGoogle ScholarPubMed
Clark, K. B. (2019). Unpredictable homeodynamic and ambient constraints on irrational decision making of aneural and neural foragers. Behavioral and Brain Sciences, 42, e40.CrossRefGoogle ScholarPubMed
Clark, K. B. (2020). Digital life, a theory of minds, and mapping human and machine cultural universals. Behavioral and Brain Sciences, 43, e98.CrossRefGoogle ScholarPubMed
Clark, K. B., & Hassert, D. L. (2013). Undecidability and opacity of metacognition in animals and humans. Frontiers in Psychology, 4, 171.CrossRefGoogle ScholarPubMed
Davies, P. C. W. (2004). Does quantum mechanics play a non-trivial role in life? BioSystems, 78, 69–79.CrossRefGoogle ScholarPubMed
Favre, M., Wittwer, A., Heinimann, H. R., Yukalov, V. I., & Sornette, D. (2016). Quantum decision theory in simple risky choices. PLoS ONE, 11(12), e0168045.CrossRefGoogle ScholarPubMed
Gödel, K. (1931). Über formal unentscheidbare Säze der Principia Mathematica und verwandter Systeme I. Monatshefte für Mathematik und Physik, 38, 173–198.CrossRefGoogle Scholar
Gollier, C. (2004). The economics of risk and time. Cambridge: The MIT Press.Google Scholar
Haith, A. M., Reppert, T. R., & Shadmehr, R. (2012). Evidence for hyperbolic temporal discounting of reward in control of movements. Journal of Neuroscience, 32, 11727–11736.CrossRefGoogle ScholarPubMed
Hu, Y., & Loo, C. K. (2014). A generalized quantum-inspired decision making model for intelligent agent. The Scientific World Journal, 2014, 240983.CrossRefGoogle ScholarPubMed
Jumarie, G. (1980). An approach to encoding in the presence of subjectivity. Journal of Information and Optimization Sciences, 1(2), 166–186.CrossRefGoogle Scholar
Jumarie, G. (1984). On the consistency between thermodynamic entropy, information entropy, and relativistic information. Cybernetica, 27(2), 93–105.Google Scholar
Jumarie, G. (1990). Relative information: Theories and applications. Springer Series in Synergetics. Berlin: Springer-Verlag. ISBN 978–3642840197.CrossRefGoogle Scholar
Kahneman, D., & Tversky, A. (1979). An analysis of decision under risk. Econometrica, 47(2), 263–292.CrossRefGoogle Scholar
Lemon, W. C. (1991). Fitness consequences of foraging behaviour in the zebra finch. Nature, 352, 153–155.CrossRefGoogle Scholar
Nielson, M. A., & Chuang, I. L. (2000). Quantum computation and quantum information. Cambridge: Cambridge University Press. ISBN 0-521-63503-9.Google Scholar
Niv, Y., Daw, N. D., Joel, D., & Dayan, P. (2007). Tonic dopamine: Opportunity costs and the control of response vigor. Psychopharmacology (Berl), 191, 507–520.CrossRefGoogle ScholarPubMed
Pothos, E. M., & Busemeyer, J. R. (2009). A quantum probability explanation for violations of “rational” decision theory. Proceedings of Biological Sciences, 276, 2171–2178.Google ScholarPubMed
Pothos, E. M., & Busemeyer, J. R. (2013). Can quantum probability provide a new direction for cognitive modeling? Behavioral and Brain Sciences, 36, 255–327.CrossRefGoogle ScholarPubMed
Reppert, T. R., Lempert, K. M., Glimcher, P. W., & Shadmehr, R. (2015). Modulation of saccade vigor during value-based decision making. Journal of Neuroscience, 35, 15369–15378.CrossRefGoogle ScholarPubMed
Shafir, E., & Tversky, A. (1992). Thinking through uncertainty: Nonconsequential reasoning and choice. Cognitive Psychology, 24, 449–474.CrossRefGoogle Scholar
Stephens, D. W., & Krebs, J. R. (1986). Foraging theory. Princeton University Press.Google Scholar
Stott, H. P. (2006). Cumulative prospect theory's functional menagerie. Journal of Risk and Uncertainty, 32, 101–130.CrossRefGoogle Scholar
Todorov, E., & Jordan, M. I. (2002). Optimal feedback control as a theory of motor coordination. Nature Neuroscience, 5, 1226–1235.CrossRefGoogle ScholarPubMed
Tressoldi, P. E., Maier, M. A., Buechner, V. L., & Khrennikov, A. (2015). A macroscopic violation of no-signaling in time inequalities? How to test temporal entanglement with behavioral observables. Frontiers in Psychology, 6, 1061.CrossRefGoogle ScholarPubMed
Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunctive fallacy in probability judgment. Psychological Reviews, 90, 293–315.CrossRefGoogle Scholar
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297–323.CrossRefGoogle Scholar
Von Neumann, J., & Morgenstern, O. (1953). Theory of games and economic behavior. Princeton University.Google Scholar
Wang, Z., & Busemeyer, J. (2015). Reintroducing the concept of complementarity to psychology. Frontiers in Psychology, 6, 1822.CrossRefGoogle ScholarPubMed
Yearsley, J. M., & Pothos, E. M. (2014). Challenging the classical notion of time in cognition: A quantum perspective. Proceedings of the Royal Society London B: Biological Sciences, 281, 20133056.Google ScholarPubMed
Yoon, T., Jaleel, A., Ahmed, A. A., & Shadmehr, R. (2020). Saccade vigor and the subjective economic value of visual stimuli. Journal of Neurophysiology, 123, 2161–2172.CrossRefGoogle ScholarPubMed
Yukalov, V. I., & Sornette, D. (2009). Processing information in quantum decision theory. Entropy, 11, 1073–1120.CrossRefGoogle Scholar
Yukalov, V. I., & Sornette, D. (2010). Entanglement production in quantum decision making. Physics of Atomic Nuclei, 73, 559–562.CrossRefGoogle Scholar
Yukalov, V. I., & Sornette, D. (2014). Conditions for quantum interference in cognitive sciences. Topics in Cognitive Science, 6, 79–90.CrossRefGoogle ScholarPubMed