Autonomous search is a particular case of adaptive systems that improve their solving performance by modifying and adjusting themselves to the problem at hand, either by self-adaptation or by supervised adaptation. We propose a general definition and a taxonomy of search processes with respect to their computation characteristics. For this purpose, we decompose solvers into components and their configurations. Some computation rules between computation stages are used to formalize the solver modifications and adaptations. Using these rules, we then sketch out and classify some well known solvers and try to answer the question: "What is Autonomous Search?"