Effective Decision Theory
Summary
Introduces Effective Decision Theory (EDT), inspired by physics’ Effective Field Theory (EFT). Problem: Traditional Expected Utility Theory struggles with paradoxes like Pascal’s Mugging and St. Petersburg, where improbable high-impact outcomes dominate rational analysis. Solution by analogy: EFT in physics ignores phenomena beyond certain energy scales because they have negligible observable effects. EDT similarly sets a probability cutoff below which outcomes are treated as effectively zero. Core principles: (1) Practical probability threshold prevents negligible-probability scenarios from dominating; (2) Contextual adaptation — cutoff varies by decision context, stakes, data quality; (3) Coherence within defined domain, sacrificing theoretical completeness for practical effectiveness. Justification: Extremely low probabilities involve high epistemic uncertainty and modeling ambiguity. Related approaches: Formalizes Nicolausian discounting (Bernoulli’s St. Petersburg heuristic), compatible with Entropic Value at Risk (EVaR). Open questions: Rigorous threshold selection, adaptive frameworks, formal coherence.
Tags
Cross-References
- Related: The Quantum Branching Universe (QBU)
- Related: Effective Altruism Without Moral Realism
Notes
- “Effective” may echo effective altruism terminology while critiquing it
- Bridges physics to rational choice theory
- Technical/formal approach