Decision Network Context: Dynamics and Learning in Preference Formation

Recently, there has been a debate in decision-making about whether people integrate attributes such as money and probabilities into subjective values or they employ somewhat different psychological processing, without integration of attributes and decision trade-offs. In the latter decision-making is accounted for by experience with sequential events, simple binary comparisons and a threshold mechanism. Despite all the differences offered in these theories of utility formation and decisions from experience/descriptions, they share common assumption - decision makers have stable and coherent preferences, informed by consistent use of psychological processing (computational or sampling) that guide their choices between alternatives varying in risk and reward. In this research we pursued the opposite idea: people do not have underlying preferences for risk; decision-makers gate strategy selection from current context (decision-network context) and learn to select decision strategies that are most successful (effort and
reward) for a given context.