This dissertation examines bounded rationality as a tool in distributed systems of intelligent agents. We have implemented, in Java, a simulator for complex adaptive systems called CAF??. We use our framework to simulate a simple network and compare the effectiveness of bounded rationality at routing and admission control to that of a more traditional, source based, greedy routing approach. We find that the boundedly rational approach is particularly effective when user behavior is synchronized, such as occurs during breaking news releases on the World Wide Web, for example. We develop the key structures of our framework by first examining, through simulation, the behavior of boundedly rational speculators in a simple economy. We find them to be instrumental in bringing the economy quickly to price equilibrium as well as in maintaining the equilibrium in the face of changing conditions. We draw several interesting conclusions as to the key similarities between economy and computational systems and also, the situations where they differ drastically.