Quantum Probability Seen by a Classical Probabilist

Lee C. White, Emmanuel M. Pothos, Jerome R. Busemeyer

Organizational decision making is often explored with theories from the heuristics and biases research program, which have demonstrated great value as descriptions of how people in organizations make decisions. Nevertheless, rational analysis and classical probability theory are still seen by many as the best accounts of how decisions should be made and classical probability theory is the preferred framework for cognitive modelling for many researchers. The focus of this work is quantum probability theory, an alternative probabilistic framework. Results in decision making, which appear paradoxical from a perspective of classical probability theory, may make perfect sense if one adopts quantum probability theory. We review some cognitive models of decision making based on quantum probability theory. Each of these models is based on a challenge to prescription from classical probability theory. The transition from labeling a particular behavior as irrational, by classical probability standards, to (potentially) rational (or, at any rate, not fallacious), raises interesting possibilities, including that of characterizing certain heuristics in formal, probabilistic terms.

P. A. Meyer

P. A. Meyer

Revista, Zen, MATH, 10

This paper proposes a comprehensive categorical framework for unifying classical and quantum probabilistic logics. We leverage the inherent compositional and structural advantages of category theory to construct a common mathematical language capable of expressing both Kolmogorovian probability and the non-Boolean structures characteristic of quantum mechanics. By treating systems and processes as objects and morphisms within suitable monoidal categories, we demonstrate how core concepts like states, observables, measurements, and conditioning can be abstractly represented and seamlessly transitioned between classical and quantum domains. The framework utilizes probability monads for classical uncertainty and dagger compact closed categories for quantum processes, showing how these distinct structures can be seen as instances of a more general categorical paradigm. This unification not only provides a deeper foundational understanding of uncertainty across different physical theories but also opens new avenues for developing hybrid probabilistic-logical systems in fields such as artificial intelligence and quantum computation.

Andrei Yu. Khrennikov

Marius Nagy, Naya Nagy

We propose a quantum version of Tic-Tac-Toe which accurately reflects the inherent probabilistic nature of the measurement principle in quantum mechanics. We then formulate a quantum strategy which allows a quantum player to consistently win over a classical player, with a certain probability. This result can be seen as another proof of the superior computational power of a quantum system with respect to a classical one. Our investigation also reveals that the non-determinism and complexity introduced by the principles of quantum mechanics into even the most simple games make brute-force strategies considerably more difficult to implement. Consequently, games in which machines have gained the upper hand over humans may be made fair again by upgrading them to a quantum level.