Finite-state automata called transducers, which have both input and output, can be used to model simple mechanisms of biological mutation. We present a methodology whereby numerically -weighted versions of such specifications can be mechanically adapted to create string edit machines that are essentially equivalent to recurrence relations of the sort that characterize dynamic programming alignment algorithms. Based on this, we have developed a visual programming system for designing new alignment algorithms in a rapid-prototyping fashion. 1 Introduction Finite-state automata have an important place in computer science, often representing simple models of computation as the recognition or generation of strings of symbols. A wide variety of such automata have been intensively studied, including weighted automata which have numbers associated with transitions between states, and transducers which have both input and output. Allison and co-workers [2] have proposed the use of finite-stat...

This paper is an attempt to persuade you of my viewpoint by presenting a novel generic program for a certain class of optimisation problems, named sequential decision processes. This class was originally identified by Richard Bellman in his pioneering work on dynamic programming [4]. It is a perfect example of a class of problems which are very much alike, but which has until now escaped solution by a single program. Those readers who have followed some of the work that Richard Bird and I have been doing over the last five years [6, 7] will recognise many individual examples: all of these have now been unified. The point of this observation is that even when you are on the lookout for generic programs, it can take a rather long time to discover them. The presentation below will follow that earlier work, by referring to the calculus of relations and the relational theory of data types. I shall however attempt to be light on the formalism, as I do not regard it as essential to the main thesis of this paper. Undoubtedly there are other (perhaps more convenient) notations in which the same ideas could be developed. This paper does assume some degree of familiarity with a lazy functional programming language such as Haskell, Hope, Miranda

The main contribution of this thesis is a study of the dynamic programming and greedy strategies for solving combinatorial optimization problems. The study is carried out in the context of a calculus of relations, and generalises previous work by using a loop operator in the imperative programming style for generating feasible solutions, rather than the fold and unfold operators of the functional programming style. The relationship between fold operators and loop operators is explored, and it is shown how to convert from the former to the latter. This fresh approach provides additional insights into the relationship between dynamic programming and greedy algorithms, and helps to unify previously distinct approaches to solving combinatorial optimization problems. Some of the solutions discovered are new and solve problems which had previously proved difficult. The material is illustrated with a selection of problems and solutions that is a mixture of old and new. Another contribution is the invention of a new calculus, called the graph calculus, which is a useful tool for reasoning in the relational calculus and other non-relational calculi. The graph

Many formalisms have been proposed over the years to capture combinatorial optimization algorithms such as dynamic programming, branch and bound, and greedy. In 1989 Helman presented a common formalism that captures dynamic programming and branch and bound type algorithms. The formalism was later extended to include greedy algorithms. In this paper, we describe the application of automated reasoning techniques to the domain of our model, in particular considering some representational issues and demonstrating that proofs about the model can be obtained by an automated reasoning program. The long-term objective of this research is to develop a methodology for using automated reasoning to establish new results within the theory, including the derivation of new lower bounds and the discovery (and verification) of new combinatorial search strategies. 1 Introduction Many formalisms have been proposed over the years to capture combinatorial optimization algorithms such as dynami...

: We present two dynamic programming strategies for a general class of decision processes. Each of these algorithms includes among others the following graph theoretic optimization algorithms as special cases: ffl the Ford-Bellman Strategy for optimal paths in acyclic digraphs, ffl the Greedy Method for optimal forests and spanning trees in undirected graphs. In our general decision model, we define several structural properties of cost measures in order to formulate sufficient conditions for the correctness of our algorithms. Our first algorithm works as fast as the original Ford-Bellman Strategy and the Greedy Method, respectively. Our second algorithm solves a larger class of optimization problems than our first search strategy. --------------------------------------------- 1) Ernst-Moritz-Arndt-Universitat Greifswald, Fachrichtungen Mathematik/Informatik, Jahnstr. 15 a, D-17487 Greifswald, GERMANY 0 Introduction Two of the most prominent graph theoretic optimization strategies ...