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The article considers the paradigm of subjective probability and expected utility theory with respect to their applications in the theory of decision-making. Advantages and shortcomings of Savage's axiomatic in the subjective probability theory are analyzed, the models of beliefs formation are considered. The authors propose a new approach to the analysis of decision-making — a multiple priors model, where an agent attributes to each event not a single probability, but a range of probabilities.

People often wonder why economists analyse models whose assumptions are known to be false, while economists feel that they learn a lot from such exercises. We suggest that part of the knowledge generated by academic economists is case-based rather than rule-based. That is, instead of offering general rules or theories that should be contrasted with data, economists often analyse modelsthat are 'theoretical cases′, which help understand economic problems by drawinganalogies between the model and the problem. Thus, economic models, empiricaldata, experimental results and other sources of knowledge are all on equal footing, that is, they all provide cases to which a given problem can be compared. We offer complexity arguments that explain why case-based reasoning may sometimes be the method of choice and why economists prefer simple cases.