Many problems facing software engineers demand 'optimal' performance in multiple dimensions, such as computational overhead and development overhead. For these complex problems, designing an optimal solution based upon a single programming paradigm is not feasible. A more appropriate solution is to create a solution framework that embraces multiple programming paradigms, each of which is optimal for a well-defined region of the problem space. This paper proposes a theory for creating multi-paradigm software solutions that is inspired by two contributions from theoretical physics: model dependent realism and M-Theory. The proposed theoretical framework, which we call 'S-Theory', promotes the creation of actor-optimal solution frameworks, encourages technology reuse and identifies promising research directions. We use the field of sensor networks as a running example.