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Models of Affective Decision Making
Author(s) -
Caroline J. Charpentier,
JanEmmanuel De Neve,
Xinyi Li,
Jonathan P. Roiser,
Tali Sharot
Publication year - 2016
Publication title -
psychological science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.641
H-Index - 260
eISSN - 1467-9280
pISSN - 0956-7976
DOI - 10.1177/0956797616634654
Subject(s) - feeling , psychology , value (mathematics) , social psychology , function (biology) , prospect theory , cognitive psychology , loss aversion , microeconomics , economics , computer science , evolutionary biology , machine learning , biology
Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision.

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