This paper reports on an experimental test of the Principle of Optimality in dynamic decision problems. This Principle, which states that the decision-maker should always choose the optimal decision at each stage of the decision problem, conditional on behaving optimally thereafter, underlies many theories of optimal dynamic decision making, but is normally difficult to test empirically without knowledge of the decision-maker's preference function. In the experiment reported here we use a new experimental procedure to get round this difficulty, which also (...) enables us to shed some light on the decision process that the decision-maker is using if he or she is not using the Principle of Optimality - which appears to be the case in our experiments. (shrink)

Many decisions involve multiple stages of choices and events, and these decisions can be represented graphically as decision trees. Optimal decision strategies for decision trees are commonly determined by a backward induction analysis that demands adherence to three fundamental consistency principles: dynamic, consequential, and strategic. Previous research found that decision-makers tend to exhibit violations of dynamic and strategic consistency at rates significantly higher than choice inconsistency across various levels of potential reward. The current research extends these findings under new conditions; (...) specifically, it explores the extent to which these principles are violated as a function of the planning horizon length of the decision tree. Results from two experiments suggest that dynamic inconsistency increases as tree length increases; these results are explained within a dynamic approach–avoidance framework. (shrink)

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