The research project Bounded Rationality under Uncertainty deals with decision theory under uncertainty an is located at the frontier between formal philosophy, theoretical economics and applied logic. The Bayesian orthodoxy in ch...
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Descripción del proyecto
The research project Bounded Rationality under Uncertainty deals with decision theory under uncertainty an is located at the frontier between formal philosophy, theoretical economics and applied logic. The Bayesian orthodoxy in choice under uncertainty, axiomatized by L. Savage in the fifties, is currently disputed by two very different research strands : the bounded rationality program which stresses the crucial role of cognitive limitations in choice, and the Non-Expected Utility (NEU) models like those based on non-additive probabilities (Schmeidler, 1989) that try to improve behaviorally the Bayesian model. Unfortunately, there is no unification between these two research strands : usually, the boundedly rational choice models deal with choice under certainty and the NEU models abstracts from cognitive limitations in the same way that the Bayesian model does. Our general research objective is to build a bridge between these two strands of research and construct models that take cognitive and informational limitations into account. As bounded rationality manifests itself in numerous ways, one can study it with different methods. Our project will (i) focus on one type of cognitive limitations, imperfect reasoning abilities (failures of logical omniscience) and (ii) favor one general method, the axiomatic method ,that is much used in the NEU field but much less in the bounded rationality tradition. To achieve such a general objective, we will adopt a syntactic and logic-based approach and import from philosophical logic (more precisely from epistemic logic) a modeling technique known under the name of impossible worlds. This technique allows oneself to represent cognitive limitations ; we will use it to devise a boundedly rational choice model under uncertainty and provide of this model an axiomatization in termes of agent’s preferences.