This study provides a foundation for decision making with bounded rationality in economic entities from the viewpoint of evolutionary theory. To this end, first, we conducted an investment test with participants to extract behavioural learning model for activities with bounded rationality. We found that the decision-making model obtained from this behavioural science approach has, characteristics that are frequently seen in the results of observations of instances of bounded rationality; furthermore, the model presents some well-known biases in decision making, such as profit-and-loss asymmetry in risk avoidance, reference point dependency, and the asset effect. Next, using agent-based simulations, we examined whether our behaviourallearning model for activities had the capacity to become a stable strategy in a market environment where selection pressure exists. When, in response to maximum loss, a drawdown is set as an evaluation criterion for selection, the results of our simulations imply the following: (1) our decision-making model with bounded rationality has the capacity to become a stable evolutionary strategy; (2) entities with bounded rationality can survive in a competitive market. These results are antithetical to the evolutionary explanations used as a basis for rationality in traditional economics, and they indicate the possibility that many well-known biases in decision making can be derived evolutionarily from a single criterion.
Published in:
Evolutionary Computation, IEEE Transactions on
(Volume:PP
,
Issue:
99
)