(PhysOrg.com) -- Humans don’t always make the most rational decisions. As studies have shown, even when logic and reasoning point in one direction, sometimes we chose the opposite route, motivated by personal bias or simply "wishful thinking." This paradoxical human behavior has resisted explanation by classical decision theory for over a decade. But now, scientists have shown that a quantum probability model can provide a simple explanation for human decision-making - and may eventually help explain the success of human cognition overall.

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This example pay-off matrix for a Prisoner’s Dilemma game shows that defecting is the rational choice, since a player receives greater pay-offs when defecting (10 or 25) than when cooperating (5 or 20). However, if both players cooperate, each will receive a larger pay-off (20) than if both defect (10). Using a quantum probability model, scientists provide a psychological explanation for why a player might choose to cooperate without any knowledge of his opponent.

If you were asked to gamble in a game in which you had a 50/50 chance to win $200 or lose $100, would you play? In one study, participants were told that they had just played this game, and then were asked to choose whether to try the same gamble again. One-third of the participants were told that they had won the first game, one-third were told they had lost the first game, and the remaining one-third did not know the outcome of their first game. Most of the participants in the first two scenarios chose to play again (69% and 59%, respectively), while most of the participants in the third scenario chose not to (only 36% played again). These results violate the “sure thing principle,” which says that if you prefer choice A in two complementary known states (e.g., known winning and known losing), then you should also prefer choice A when the state is unknown. So why do people choose differently when confronted with an unknown state?

In a recent study, psychologists Emmanuel M. Pothos of Swansea University in the UK and Jerome R. Busemeyer of Indiana University in the US have presented an alternative framework for modeling decision-making of this kind, based on quantum probability. As they note, the original motivation for developing quantum mechanics in physics was to explain findings that seemed paradoxical from a classical point of view. Possibly, quantum theory can better explain paradoxical findings in psychology, as well. In recent years, a growing number of researchers have investigated using quantum formalism in cognitive situations, such as in modeling human judgment and perception. Pothos and Busemeyer’s results are published in a recent issue of Proceedings of the Royal Society B.

“A few decades ago, Tversky and Kahneman (1974) challenged ubiquitous assumptions regarding what is the most suitable framework for modeling human cognition,” Busemeyer told PhysOrg.com. “Until then, most psychologists sought to understand cognition using classic probability theory. In our paper we raise the question, which mathematical framework is most appropriate for cognitive modeling? In this article, for the first time, we present a fundamentally different, and more powerful, approach to probabilistic models of cognition, based on quantum principles. Employing minimal assumptions, we derive a Hamiltonian directly from the parameters of the problem (e.g., the payoffs associated with different actions) and known general principles of cognition (e.g., a well known phenomenon of cognitive dissonance); every step in our model is psychologically interpreted and rigorously justified.”

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