A robust measure of complexity

TL;DR

This paper proposes a new belief-based complexity measure that accounts for both difficulty and ex ante uncertainty, providing a more comprehensive understanding of task complexity and effort required.

Contribution

It introduces a robust complexity measure based on belief and probability, fully characterizes the task order, and links optimal information acquisition to task complexity.

Findings

Complexity depends on difficulty and ex ante uncertainty.

For any optimally informed task, a more complex task requires less effort.

The measure characterizes the order of tasks based on success probabilities.

Abstract

We introduce a robust belief-based measure of complexity. The idea is that task A is deemed more complex than task B if the probability of solving A correctly is smaller than the probability of solving B correctly regardless of the reward. We fully characterize the corresponding order over the set of tasks. The main characteristic of this relation is that it depends, not only on difficulty (like most complexity definitions in the literature) but also on ex ante uncertainty. Finally, we show that for every task for which information is optimally acquired, there exists a more complex task which always induces less effort regardless of the reward.