In the psychological and biological fields, it is commonly assumed that the mind disposes of a repertoire of different strategies, which it utilizes in solving cognitive and behavioral tasks. This repertoire is also known as the mind's toolbox. However, the mechanisms underlying the selection of the proper strategy from the toolbox are still not well known. The framework of strategy selection as rational meta reasoning introduced by F. Lieder & T. L. Griffith, 2017 assumes that the strategy selection from the toolbox is based on a subjective assessment of two key variables, which are a trade off against each other:
The strategy Accuracy for a given task.
The Costs necessary to implement the strategy.
However, the accuracy and costs of a strategy in a given situation are usually not directly accessible to the decision maker and need to be inferred.
In this project we aim to contribute to the Ecologically Rational Strategy Selection through providing a better understanding by focusing on how the crucial inferences of the framework's parameters for strategy selection are cognitively and computationally implemented and how they can be improved.