Running Head: Computational Model of Decision Weights
نویسندگان
چکیده
During the past 50 years, a number of paradoxes have led to the downfall of expected utility theory as a viable description of decision making. Recently, rankdependent theories (e.g. cumulative prospect theory) have arisen as the ―leading‖ descriptive approach. A key component of these theories is the decision weight that reflects the importance of consequences when evaluating an action. Several researchers have had success in fitting functional forms for decision weights to account for empirical data. However, little is known about the cognitive source of these weights. The current work presents a computational model that derives decision weights from elementary attentional processing mechanisms. It is shown that the attention process model provides a coherent explanation for several robust phenomena including some that cannot be explained by rank-dependent utility theories.
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