{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ergodicity-breaking-reveals-time-optimal","title":"Ergodicity-breaking reveals time optimal decision making in humans","arxiv_id":"1906.04652","date":"2020-09-25","proceeding":null,"authors":[],"abstract":"Ergodicity describes an equivalence between the expectation value and the\ntime average of observables. Applied to human behaviour, ergodic theories of\ndecision-making reveal how individuals should tolerate risk in different\nenvironments. To optimise wealth over time, agents should adapt their utility\nfunction according to the dynamical setting they face. Linear utility is\noptimal for additive dynamics, whereas logarithmic utility is optimal for\nmultiplicative dynamics. Whether humans approximate time optimal behavior\nacross different dynamics is unknown. Here we compare the effects of additive\nversus multiplicative gamble dynamics on risky choice. We show that utility\nfunctions are modulated by gamble dynamics in ways not explained by prevailing\neconomic theory. Instead, as predicted by time optimality, risk aversion\nincreases under multiplicative dynamics, distributing close to the values that\nmaximise the time average growth of wealth. We suggest that our findings\nmotivate a need for explicitly grounding theories of decision-making on ergodic\nconsiderations.","url_abs":"http://arxiv.org/abs/1906.04652v4","url_pdf":"http://arxiv.org/pdf/1906.04652v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"ergodicity-breaking-reveals-time-optimal","repo_url":"https://github.com/ollie-hulme/ergodicity-breaking-choice-experiment","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"decision-making","task_name":"Decision Making"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}