 Computability, or the question whether a function can be computed, is not the only question that interests computer scientists. Beginning especially in the 1960s (Cobham 1965; Edmonds 1965; Hartmanis and Stearns 1965), the question of the cost of computing a function (which was to some extent already anticipated in 1956 by Gödel) also came to be of great importance. This cost, also known as  computational complexity,  is measured naturally in the physical resources (e.g., time, space, energy) invested in order to solve the computational problem at hand. Computer scientists classify computational problems according to the way their cost function behaves as a function of their input size, \(n\) (the number of bits required to store the input) and in particular, whether it increases exponentially or polynomially with \(n\). Tractable problems are those which can be solved in polynomial cost, while intractable problems are those which can only be solved with exponential cost (the former solutions are commonly regarded as efficient although an exponential-time algorithm could turn out to be more efficient than a polynomial-time algorithm for some range of input sizes).