Complexity and Procedural Choice
通过简单的实验赌博任务，检验了有限理性中“自动机”方法的核心思想，发现大多数被试倾向于使用更简单的决策程序，而当计算机帮助追踪状态时，被试会转向最优的复杂规则。
We test the core ideas of the “automata” approach to bounded rationality, using simple experimental bandit tasks. Optimality requires subjects to use a moderately complex decision procedure, but most subjects in our baseline condition instead use simpler (often suboptimal) procedures that economize on “states” in the algorithmic structure of the rule. When we artificially remove the mental costs of tracking states by having the computer track and organize past events, subjects abandon these simpler rules and use maximally complex optimal rules instead. The results thus suggest that the main type of complexity described in the automata literature fundamentally influences behavior.