QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision

TL;DR

This paper introduces QuLBIT, a quantum-inspired framework for cognitive decision-making that explains human irrationality and paradoxes using quantum interference effects to analyze belief uncertainty.

Contribution

It presents a novel unified quantum-like model for cognition that enhances explanatory power over existing quantum approaches in decision-making.

Findings

Successfully explains violations of the Sure Thing Principle.

Uses quantum interference to quantify and interpret decision-maker's uncertainty.

Provides a comprehensive framework integrating quantum effects into cognitive modeling.

Abstract

This paper provides the foundations of a unified cognitive decision-making framework (QulBIT) which is derived from quantum theory. The main advantage of this framework is that it can cater for paradoxical and irrational human decision making. Although quantum approaches for cognition have demonstrated advantages over classical probabilistic approaches and bounded rationality models, they still lack explanatory power. To address this, we introduce a novel explanatory analysis of the decision-maker's belief space. This is achieved by exploiting quantum interference effects as a way of both quantifying and explaining the decision-maker's uncertainty. We detail the main modules of the unified framework, the explanatory analysis method, and illustrate their application in situations violating the Sure Thing Principle.