Human cognition has been shown to occur within well-defined time frames that are arithmetically related to the number of serial decisions needed to perform the task. The power law of learning is a phenomenological measure of this observation. When a task is first presented to an agent, the agent must deliberate over every move resulting in slow performance. As the agent learns, fewer and fewer serial decisions need to be made and the agent performs faster. Strict limits have been found in humans that limit the ability to make small numbers of serial decisions.
This data illustrates the real-time constraint on cognition: "There are available only ~100 operation times (two minimum system levels) to attain cognitive behavior out of neural-circuit technology." This constraint shows that the interaction between distinct computational units (whether in a parallel or serial organization) is minimal.
The data also provides some insight on the decomposition of perception, delivery of symbols to memory, deliberation, and action. This decomposition is not discussed here, but can be found in Newell's Unified Theory of Cognition. It also suggests that the hierarchy (or heterarchy) of deliberation consists of serial and parallel processes that are configured such that these limits emerge.
Many architectures of general intelligence seek to explain the hierarchy or to meet the constraint in order to better understand human cognition.