Biological brains are capable of adaptive behavior to sustain performance in tasks in the face of increasingly difficult constraints. We present a task with varying conditions of resource and time constraints. We compare our heuristic and neural network models to human data and speculate about dynamic mechanisms of action selection.

Biological brains are capable of adaptive behavior to sustain performance on tasks in the face of increasingly difficult constraints. Precisely how this performance is achieved, especially under demanding real-time constraint, is an important problem in the study of cognition. Brains are embedded in and constrained by their environments. The brain/environment pair together form a coupled dynamical system that mutually influence and react to one another. We can begin to understand how such performance is achieved by studying real behavior on constrained tasks, and modeling this behavior. In this article we present a task with varying conditions of time and resource constraint. We present data collected on humans performing the task under such constraint. We compare models that we have developed of this behavior generation to human performance. Finally we speculate on some of the mechanisms of chaotic neurodynamics that may be involved in the flexible generation of behavior under constraint.