{"ID":2838754,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.17714","arxiv_id":"2511.17714","title":"Learning the Value of Value Learning","abstract":"Standard decision frameworks address uncertainty about facts but assume fixed options and values. We extend the Jeffrey-Bolker framework to model refinements in values and prove a value-of-information theorem for axiological refinement. In multi-agent settings, we establish that mutual refinement will characteristically transform zero-sum games into positive-sum interactions and yield Pareto-improvements in Nash bargaining. These results show that a framework of rational choice can be extended to model value refinement. By unifying epistemic and axiological refinement under a single formalism, we broaden the conceptual foundations of rational choice and illuminate the normative status of ethical deliberation.","short_abstract":"Standard decision frameworks address uncertainty about facts but assume fixed options and values. We extend the Jeffrey-Bolker framework to model refinements in values and prove a value-of-information theorem for axiological refinement. In multi-agent settings, we establish that mutual refinement will characteristicall...","url_abs":"https://arxiv.org/abs/2511.17714","url_pdf":"https://arxiv.org/pdf/2511.17714v5","authors":"[\"Alex John London\",\"Aydin Mohseni\"]","published":"2025-11-21T19:06:30Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.GT\"]","methods":"[]","has_code":false}