Exploring an information-based approach to computation and computational complexity

We present the background and justi cation for a new approachto studying computation and computational complexity. We focus on categories of problems and categories of solutions which provide the logical de nition on which to base an algorithm. Computational capability is introduced via a formalization of computation termed a model of computation. The concept of algorithm is formalized using the methods of Traub, Wasilkowski and Wo zniakowski, from which we can formalize the di erences between deterministic, non-deterministic, and heuristic algorithms. Finally, we introduce a measure of complexity: the Hartley entropy measure. We provide many examples to amplify the concepts introduced. 1 Our Goals That which you cannot explain, you do not understand." attributed to Albert Camus We, as computer scientists, should be at least mildly concerned over the quality of software. As rst documented by Charles Perrow 21 and so aptly continued by Peter Neuman in comp.risks, complexity is at ...

• Type: Conference
• Year: 2000
• Where: ACMSE
• Authors: D. E. Stevenson
• Keywords: ACMSE 2000, Approachto Studying Computation, Computational Complexity, Hartley Entropy Measure, Theoretical Computer Science