Sterman (1989) proposed that decision makers misperceive
the feedback provided by dynamically complex environments,
and questioned whether people can learn to make effective
decisions in such environments. We provide empirical
evidence of learning in a well-known dynamic environment
called the beer game. We then describe a preliminary version
of an instance-based, dynamic decision making model built
using the ACT-R cognitive architecture. The model mimics
the general patterns of human behavior observed for
aggregate performance across trials and local performance
within trials. Implications for research on dynamic decision
making are summarized.