The purpose of this study is to research and examine the processes of living complex adaptive systems in the context of an uncertain and ever-changing environment. Drawing from the works of William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive systems as control loops and the processes of adaptive systems as a Markov process. Using this model, the study concluded that systems would return to the same relative equilibrium point, expressed in terms of requisite variety, with their environment unless they changed the rate of relative adaptation into their favor by creating asymmetry in their control loops. This means, the system had to affect the environment more than the environment could affect it. The study found that a system's representation of their external situation determines their ability to learn. Learning then determines the ability of the system to adapt and adjust their structures to achieve asymmetry in their control loops and a position of relative advantage at equilibrium. The study also found a system can achieve regulation by adapting its goals and changing the variables considered essential, thereby achieving asymmetry by assuming a state that potentially resets the selection criteria for fitness.