Network approach for decision making under risk-How do we choose among probabilistic options with the same expected...

Area of Science:

• Decision Science
• Cognitive Psychology
• Network Theory

Background:

• Conventional decision theory posits maximizing expected utility under risk.
• Existing theories struggle to explain choices between options with identical expected utility.
• Human decision-making under risk often appears irrational when evaluated by expected utility alone.

Purpose of the Study:

• To address the ambiguity in decision theory regarding options with equal expected utility.
• To develop a network-based approach for calculating time-dependent goal achievement probabilities.
• To provide a mathematical framework explaining choices that deviate from maximizing expected utility.

Main Methods:

• Introduction of 'goal' and 'time' factors into a network model.
• Development of strategies for calculating time-dependent probabilities of reaching a goal.
• Mathematical analysis to identify conditions leading to selection of lower expected utility options.

Main Results:

• A novel network approach effectively reduces ambiguity in decision strategies.
• The model successfully calculates time-dependent probabilities for goal attainment.
• A mathematical foundation is established for choices that prioritize factors beyond immediate expected utility.

Conclusions:

• The proposed network approach offers a more nuanced understanding of decision-making under risk.
• Apparent irrationality in human choices may stem from a rational consideration of time and goals.
• This framework suggests that humans exhibit foresight-based rationality in their decisions.