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An automatic method for discovering rational heuristics for risky choice
Abstract
What is the optimal way to make a decision given that yourtime is limited and your cognitive resources are bounded? Toanswer this question, we formalized the bounded optimal de-cision process as the solution to a meta-level Markov deci-sion process whose actions are costly computations. We ap-proximated the optimal solution and evaluated its predictionsagainst human choice behavior in the Mouselab paradigm,which is widely used to study decision strategies. Our compu-tational method rediscovered well-known heuristic strategiesand the conditions under which they are used, as well as novelheuristics. A Mouselab experiment confirmed our model’smain predictions. These findings are a proof-of-concept thatoptimal cognitive strategies can be automatically derived as therational use of finite time and bounded cognitive resources.
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