Ergodicity-breaking reveals time optimal decision making in humans
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- Ergodicity-breaking reveals time optimal decision making in humans
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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 optimise 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 maximise 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.
Original language | English |
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Article number | e1009217 |
Journal | PLOS Computational Biology |
Volume | 17 |
Issue number | 9 |
ISSN | 1553-734X |
DOIs | |
Publication status | Published - 2021 |
Bibliographical note
Publisher Copyright:
Copyright: © 2021 Meder et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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