The title of this session pitting Dynamic Programming against Control Theory is misleading since dynamic programming (DP) is an integral part of the discipline of control theory. However, it is timely to discuss the relative merits of DP and other empirical solution approaches to control problems in agricultural economics, and equally importantly, how control theory can be used to pose more use...

This study proposed multipath architecture for a dynamic (DP) programming approach to solve the problem of the uncertain starting points in dynamic programming. The starting points of those paths are selected from the local maximum of onset detection function and beginning interval of excerpts. We also utilize the tempi of tempo estimation to give the guidance of the beat tracking. Index Terms ...

In several of the earliest papers on dynamic programming (DP), reference was made to the possibility that the DP approach might be used to advise players on the optimal strategy for board games such as chess. Since these papers in the 1950s, there have been many attempts to develop such strategies, drawing on ideas from DP and other branches of mathematics. This paper presents a survey of those...

Dynamic programming (DP) is a popular technique for contour detection, particularly in biomedical image analysis. Although gradient information is typically used in such methods, it is not always a reliable measure to work with and there is a strong need of non-gradient based methods. In this paper we present a general framework for region based contour detection by dynamic programming. It is b...

Dynamic Programming (DP) is an important technique used in solving optimization problems. A close correspondence between DP recurrences and Constraint Handling Rules with rule priorities (CHR) yields natural implementations of DP problems in CHR. In this work, we evaluate different implementation techniques with respect to their runtime. From our results we derive a set of guidelines for implem...

Various methods have been used to economically design wastewater and stormwater collection systems. In this article, Discrete Differential Dynamic Programming (DDDP) which is a subsection of dynamic programming (DP) was used. For each pipe network, various alternatives such as depth and slope of pipe laying and various diameters could be considered to satisfy hydraulic and engineering constrain...

Binary and multivalued decision diagrams are closely related to dynamic programming (DP) but differ in some important ways. This paper makes the relationship more precise by interpreting the DP state transition graph as a weighted decision diagram and incorporating the state-dependent costs of DP into the theory of decision diagrams. It generalizes a well-known uniqueness theorem by showing tha...

This paper describes simple DP (dynamic programming) algorithms for RNA secondary structure prediction with pseudoknots, for which no explicit DP algorithm had been known. Results of preliminary computational experiments are described too.

Most contemporary database systems query optimizers exploit System-R’s bottom-up dynamic programming method (DP) to find the optimal query execution plan (QEP) without evaluating redundant subplans. The distinguished exceptions are Volcano/Cascades using transforms to generate new plans according to a topdown approach. As recent research has revealed, bottom-up dynamic programming can improve p...