Learning the Value of Value Learning

TL;DR

This paper extends decision theory frameworks to model how values can be refined and demonstrates the positive effects of mutual value refinement in multi-agent interactions.

Contribution

It introduces a formalism for axiological refinement and proves a value-of-information theorem within this context.

Findings

Mutual value refinement can turn zero-sum games into positive-sum interactions.

Axiological refinement leads to Pareto improvements in Nash bargaining.

The framework unifies epistemic and axiological refinement in rational choice.

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.