Brain's Strategy for Problem-Solving Amid Imperfection
A study by MIT reveals that humans use flexible strategies like hierarchical and counterfactual reasoning to solve complex problems, such as predicting a ball's path in a maze, by breaking tasks into manageable steps and revising choices based on memory reliability. These strategies are influenced by individual memory capacity and task demands, and are mirrored by neural network models under similar constraints.