Includes bibliographical references and index.

Expected Value Maximisation (EVM) is the idea that, under axiological uncertainty, one option is better than another if and only if it has the greater expected value across different axiologies. However, the expected value of an option depends on quantitative facts about probability and value, particularly on how values compare across different axiologies. We need to clarify what it means for such facts to hold. Furthermore, EVM is not self-evident, and an argument is needed to support its validity. This book introduces an axiomatic approach to address these concerns. It explains what EVM means through representation theorems: intertheoretic comparisons can be understood based on facts about which options are better than others, and similarly for intratheoretic comparisons and axiological probabilities. Additionally, the book provides a systematic argument for the truth of EVM, demonstrating that the theory can be justified using simple axioms. The result is a formally rigorous and philosophically persuasive extension of standard decision theory, offering a fresh perspective on the problem of axiological or normative uncertainty.