Savage's sure-thing principle and subsequent work by Machina show that agents facing genuine uncertainty (not risk) cannot assign meaningful probabilities to novel strategic environments.

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Genuine uncertainty(as contrasted with theoretical certainty): A real situation where you don't have complete information and can't be totally sure what's true or what will happen.
Machina(as a scholar referenced in decision theory): Mark Machina is an economist who built on Savage's work by showing that people don't always follow the sure-thing principle when making real decisions under uncertainty.
Meaningful probabilities(as used in probability and decision theory): Reliable numbers representing the actual likelihood of different outcomes—numbers you can trust and use to make good decisions.
Novel strategic environments(as used in game theory and decision theory): Completely new and unique situations where people interact with each other, and nobody has faced this exact scenario before, so there's no clear playbook.

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