TY - JOUR
T1 - Economic irrationality is optimal during noisy decision making
AU - Tsetsos, Konstantinos
AU - Moran, Rani
AU - Moreland, James
AU - Chater, Nick
AU - Usher, Marius
AU - Summerfield, Christopher
N1 - Funding Information:
This work was supported by a British Academy/Leverhulme Trust award (to K.T.); European Research Council (ERC), Economic and Social Research Council, Research Councils UK, and Leverhulme Trust awards (to N.C.); a German-Israeli Science Foundation grant and a Leverhulme Trust Visiting Professorship (to M.U.); and an ERC award (to C.S.).
PY - 2016/3/15
Y1 - 2016/3/15
N2 - According to normative theories, reward-maximizing agents should have consistent preferences. Thus, when faced with alternatives A, B, and C, an individual preferring A to B and B to C should prefer A to C. However, it has been widely argued that humans can incur losses by violating this axiom of transitivity, despite strong evolutionary pressure for reward-maximizing choices. Here, adopting a biologically plausible computational framework, we show that intransitive (and thus economically irrational) choices paradoxically improve accuracy (and subsequent economic rewards) when decision formation is corrupted by internal neural noise. Over three experiments, we show that humans accumulate evidence over time using a "selective integration" policy that discards information about alternatives with momentarily lower value. This policy predicts violations of the axiom of transitivity when three equally valued alternatives differ circularly in their number of winning samples. We confirm this prediction in a fourth experiment reporting significant violations of weak stochastic transitivity in human observers. Crucially, we show that relying on selective integration protects choices against "late" noise that otherwise corrupts decision formation beyond the sensory stage. Indeed, we report that individuals with higher late noise relied more strongly on selective integration. These findings suggest that violations of rational choice theory reflect adaptive computations that have evolved in response to irreducible noise during neural information processing.
AB - According to normative theories, reward-maximizing agents should have consistent preferences. Thus, when faced with alternatives A, B, and C, an individual preferring A to B and B to C should prefer A to C. However, it has been widely argued that humans can incur losses by violating this axiom of transitivity, despite strong evolutionary pressure for reward-maximizing choices. Here, adopting a biologically plausible computational framework, we show that intransitive (and thus economically irrational) choices paradoxically improve accuracy (and subsequent economic rewards) when decision formation is corrupted by internal neural noise. Over three experiments, we show that humans accumulate evidence over time using a "selective integration" policy that discards information about alternatives with momentarily lower value. This policy predicts violations of the axiom of transitivity when three equally valued alternatives differ circularly in their number of winning samples. We confirm this prediction in a fourth experiment reporting significant violations of weak stochastic transitivity in human observers. Crucially, we show that relying on selective integration protects choices against "late" noise that otherwise corrupts decision formation beyond the sensory stage. Indeed, we report that individuals with higher late noise relied more strongly on selective integration. These findings suggest that violations of rational choice theory reflect adaptive computations that have evolved in response to irreducible noise during neural information processing.
KW - Choice optimality
KW - Decision making
KW - Evidence accumulation
KW - Irrationality
KW - Selective integration
UR - http://www.scopus.com/inward/record.url?scp=84961859331&partnerID=8YFLogxK
U2 - 10.1073/pnas.1519157113
DO - 10.1073/pnas.1519157113
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AN - SCOPUS:84961859331
SN - 0027-8424
VL - 113
SP - 3102
EP - 3107
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 11
ER -