Open AccessErgodicity-breaking reveals time optimal decision making in humans
Author(s) -
D. Meder,
Finn Rabe,
Tobias Morville,
Kristoffer Hougaard Madsen,
Magnus Koudahl,
Raymond J. Dolan,
Hartwig R. Siebner
Publication year - 2021
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1009217
Subject(s) - multiplicative function , ergodicity , ergodic theory , equivalence (formal languages) , bellman equation , function (biology) , expected utility hypothesis , dynamics (music) , mathematics , logarithm , mathematical economics , econometrics , computer science , mathematical optimization , statistics , psychology , mathematical analysis , pedagogy , discrete mathematics , evolutionary biology , biology
Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimize wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theories. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximize the time average growth of in-game wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.