Abstract
In the face of limited computational resources, bounded rational decision theory predicts that information-processing should be concentrated on actions that make a significant contribution in terms of the utility achieved. Accordingly, information-processing can be simplified by choosing stereotypic actions that lead to satisfactory performance over a range of different inputs rather than choosing a specific action for each input. Such a set of similar inputs with similar action responses would then correspond to an abstraction that can be harnessed with possibly negligible loss in utility, but with potentially considerable savings in information-processing effort. Here we test this prediction in an identification task, where human subjects were asked to estimate the roundness of ellipses varying from a straight line to a perfect circle. Crucially, when reporting their estimates, subjects could choose between three different levels of precision corresponding to three levels of abstraction in a decision-making hierarchy. To induce changes in level selection, we manipulated the information-processing resources available at the perceptual and action stages by varying the difficulty of identifying the stimulus and by enforcing different response times in the action stage. In line with theoretical predictions, we find that subjects adapt their abstraction level depending on the available resources. We compare subjects' behavior to the maximum efficiency predicated by the bounded rational decision-making model and investigate possible sources of inefficiency.
Highlights
Consider the following guessing game where you have to identify different animals drawn from a sample set of photographs
A perfectly rational decision-maker with unlimited resources would choose actions according to a∗(w) = arg maxa U(w, a), which can be obtained as the unbounded limit case of a bounded rational decisionmaker with information constraints (Ortega and Braun, 2011; Ortega et al, 2014; Genewein et al, 2015) choosing according to a distribution given by p∗(a|w) = arg max Ep(w,a)[U(w, a)] DKL p(a|w) p0(a) ≤ K, p(a|w)
Our experiment is a hierarchically organized absolute identification task involving two information-processing stages, stimulus perception and action planning, where action planning again consists of two stages, choosing a level of abstraction and identifying the stimulus given that level
Summary
Consider the following guessing game where you have to identify different animals drawn from a sample set of photographs. Assume that the sample set includes specimens, such as different kinds of cats (e.g., Persian, Siamese), dogs (e.g., German Shepherd, Rottweiler), snakes (e.g., Ball Python, Corn Snake), lizards (e.g., Chameleon, Leopard Gecko), frogs (e.g., Poison Dart Frog, European Tree Frog), and salamanders (e.g., Axolotl, Fire Salamander). When shown a particular exemplar, you can choose to respond with the precise name of the specimen (e.g., Rottweiler) or you can content yourself with identifying a subset corresponding to an abstract category Dog) or even a larger subset corresponding to a more abstract super-category (e.g., Mammal, Reptile, or Amphibian). Such a payment scheme naturally affords different levels of abstraction, since it allows for generic responses for various subsets of exemplars. In the absence of informationprocessing limitations—in our example the availability of at least
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