Abstract

Decision making (DM) is a preferences-driven choice among available actions. Under uncertainty, Savage’s axiomatisation singles out Bayesian DM as the adequate normative framework. It constructs strategies generating the optimal actions, while assuming that the decision maker rationally tries to meet her preferences. Descriptive DM theories have observed numerous deviations of the real DM from normative recommendations. The explanation of decision-makers’ imperfection or non-rationality, possibly followed by rectification, is the focal point of contemporary DM research. This chapter falls into this stream and claims that the neglecting a part of the behaviour of the closed DM loop is the major cause of these deviations. It inspects DM subtasks in which this claim matters and where its consideration may practically help. It deals with: (i) the preference elicitation; (ii) the “non-rationality” caused by the difference of preferences declared and preferences followed; (iii) the choice of proximity measures in knowledge and preferences fusion; (iv) ways to a systematic design of approximate DM; and (v) the control of the deliberation effort spent on a DM task via sequential DM. The extent of the above list indicates that the discussion offers more open questions than answers, however, their consideration is the key element of this chapter. Their presentation is an important chapter’s ingredient.

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