Complexity, self-organization and selection

Recent work on self organization promises an explanation of complex order w hich is independent of adaptation. Self-organizing systems are complex syst ems of simple units, projecting order as a consequence of localized and gen erally nonlinear interactions between these units. Stuart Kauffman offers o ne variation on the theme of self-organization, offering what he calls a "s tatistical mechanics" for complex systems. This paper explores the explanat ory strategies deployed in this "statistical mechanics," initially focusing on the autonomy of statistical explanation as it applies in evolutionary s ettings and then turning to Kauffman's analysis. Two primary morals emerge as a consequence of this examination: first, the view that adaptation and s elf-organization should be seen as competing theories or models is misleadi ng and simplistic; and second, while we need a synthesis treating self-orga nization and adaptation as geared toward different problems, at different l evels of organization, and deploying different methods, we do not yet have such a synthesis.