The article discusses a new way to make decisions when we don't have all the information we need. Instead of using math formulas, the researchers suggest using a model based on natural selection and quantum theory. This model learns from past experiences to help us make better decisions in the future. Unlike other theories that rely on probability, this approach focuses on machine learning and rewards or punishes decision-makers to help them improve. The model doesn't use traditional methods like differential equations or transition probabilities, but instead uses quantum decision trees to simulate how people make choices. By choosing strategies from these trees and maximizing expected value, decision-makers can make more informed decisions.