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A communication system must operate in a continuously varying RF environment that depends on multiple parameters that are inter-related and non-linearly coupled. The communication system must be able to adapt to the varying RF conditions. "Cognitive Radios" are being developed to address this issue. This paper discusses the use of Genetic Algorithms (GA) to implement the adaptive processes for a cognitive radio and the associated RF design optimization in a varying RF environment. Specifically GAs are used to solve the optimization of RF parameters for a tactical wireless network. In particular, a Fitness Measure is derived to provide a figure of merit for the performance of the GA in relation to overall RF performance. Additionally, a chromosome structure is derived to consist of "RF genes". Each gene is a binary string representing some aspect or parameter of the RF environment. Finally the GA determines a set of RF parameters for optimal radio communications in the varying RF environment.