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Memoirs of the Faculty of Science, Kyushu University. Series A, Mathematics, 1976 openaire +3 more sources
Robust Dynamic Programming [PDF]
Mathematics of Operations Research, 2005 In this paper we propose a robust formulation for discrete time dynamic programming (DP). The objective of the robust formulation is to systematically mitigate the sensitivity of the DP optimal policy to ambiguity in the underlying transition probabilities.
Garud Iyengar
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Mathematics of Operations Research, 2018
We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and upper bounds ensures that the method is applicable even
Christian Bender +2 more
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We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and upper bounds ensures that the method is applicable even
Christian Bender +2 more
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Aggregation in Dynamic Programming
Operations Research, 1987Reducing the size of a dynamic program through state aggregation can significantly reduce both the data and the computation time required to solve a problem. We develop a new algorithm that combines state aggregation and disaggregation steps within a single-pass procedure. The solution obtained is automatically feasible for the original problem.
James C. Bean +2 more
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Explainable dynamic programming
Journal of Functional Programming, 2021Abstract In this paper, we present a method for explaining the results produced by dynamic programming (DP) algorithms. Our approach is based on retaining a granular representation of values that are aggregated during program execution. The explanations that are created from the granular representations can answer questions of why one
Martin Erwig, Prashant Kumar
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Dynamic programming as multiagent programming
1992We show that the search technique of dynamic programming models a form of multiagent computation characterized by the interaction of cooperating/competing agents. For this reason, dynamic programming algorithms can be easily implemented in an object-oriented concurrent language environment.
Jean-Marc Andreoli +2 more
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Dynamic program parallelization
ACM SIGPLAN Lisp Pointers, 1992Static program analysis limits the performance improvements possible from compile-time parallelization. Dynamic program parallelization shifts a portion of the analysis from complie-time to run-time, thereby enabling optimizations whose static detection is overly expensive or impossible. Lambda tagging
Huelsbergen, Lorenz, Larus, James R.
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Proceedings of the Second IEEE Symposium on Parallel and Distributed Processing 1990, 1994
Recurrence formulations for various problems, such as finding an optimal order of matrix multiplication, finding an optimal binary search tree, and optimal triangulation of polygons, assume a similar form. A. Gibbons and W. Rytter (1988) gave a CREW PRAM algorithm to solve such dynamic programming problems.
Shou-Hsuan Stephen Huang +2 more
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Recurrence formulations for various problems, such as finding an optimal order of matrix multiplication, finding an optimal binary search tree, and optimal triangulation of polygons, assume a similar form. A. Gibbons and W. Rytter (1988) gave a CREW PRAM algorithm to solve such dynamic programming problems.
Shou-Hsuan Stephen Huang +2 more
openaire +3 more sources