Mind and environment evolve in tandem-almost a platitude. Much of judg
ment and decision making research, however, has compared cognition to
standard statistical models, rather than to how well it is adapted to
its environment. The author argues two points. First, cognitive algori
thms are tuned to certain information formats, most likely to those th
at humans have encountered during their evolutionary history. In parti
cular, Bayesian computations are simpler when the information is in a
frequency format than when it is in a probability format. The author i
nvestigates whether frequency formats can make physicians reason more
often the Bayesian way. Second, cognitive algorithms need to operate u
nder constraints of limited time, knowledge, and computational power,
and they need to exploit the structures of their environments. The aut
hor describes a fast and frugal algorithm, Take The Best, that violate
s standard principles of rational inference but can be as accurate as
sophisticated ''optimal'' models for diagnostic inference.