Optimizing the depth and the direction of prospective planning using information values

摘要

Author summary When faced with several choices in complex environments like chess, thinking about all the potential consequences of each choice, infinitely deep into the future, is simply impossible due to time and cognitive limitations. An outstanding question is what is the best direction and depth of thinking about the future? Here we propose a mathematical algorithm that computes, along the course of planning, the benefit of thinking another step in a given direction into the future, and compares that with the cost of thinking in order to compute the net benefit. We show that this algorithm is consistent with several behavioral patterns observed in humans and animals, suggesting that they, too, make efficient use of their time and cognitive resources when deciding how deep to think.