Learning the Value of Value Learning

• URL: http://arxiv.org/abs/2511.17714v1
• Date: Fri, 21 Nov 2025 19:06:30 GMT
• Title: Learning the Value of Value Learning
• Authors: Alex John London, Aydin Mohseni,
• Abstract summary: We extend the Jeffrey-Bolker framework to model refinements in values and prove a value-of-information theorem for axiological refinement.<n>In multi-agent settings, we establish that mutual refinement will characteristically transform zero-sum games into positive-sum interactions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Standard decision frameworks addresses uncertainty about facts but assumes fixed 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 yields Pareto-improving Nash bargains. These results show that a framework of rational choice can be extended to model value refinement and its associated benefits. 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.

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