Results 1 to 10 of about 100,788 (264)
Empirical Dynamic Programming [PDF]
Mathematics of Operations Research, 2016 We propose empirical dynamic programming algorithms for Markov decision processes. In these algorithms, the exact expectation in the Bellman operator in classical value iteration is replaced by an empirical estimate to get “empirical value iteration” (EVI).
William B. Haskell 0001 +2 more
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Dynamic Programming on Nominal Graphs [PDF]
Electronic Proceedings in Theoretical Computer Science, 2015 Many optimization problems can be naturally represented as (hyper) graphs, where vertices correspond to variables and edges to tasks, whose cost depends on the values of the adjacent variables. Capitalizing on the structure of the graph, suitable dynamic
Nicklas Hoch +2 more
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YADPF: A reusable deterministic dynamic programming implementation in MATLAB
SoftwareX, 2022 This paper introduces the YADPF package, a collection of reusable MATLAB functions to solve deterministic discrete-time optimal control problems using a dynamic programming algorithm.
Auralius Manurung +2 more
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DynaProg: Deterministic Dynamic Programming solver for finite horizon multi-stage decision problems
SoftwareX, 2021 DynaProg is an open-source MATLAB toolbox for solving multi-stage deterministic optimal decision problems using Dynamic Programming. This class of optimal control problems can be solved with Dynamic Programming (DP), which is a well-established optimal ...
Federico Miretti +2 more
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State of the Art of Adaptive Dynamic Programming and Reinforcement Learning
CAAI Artificial Intelligence Research, 2022 This article introduces the state-of-the-art development of adaptive dynamic programming and reinforcement learning (ADPRL). First, algorithms in reinforcement learning (RL) are introduced and their roots in dynamic programming are illustrated.
Derong Liu, Mingming Ha, Shan Xue
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Versatile and declarative dynamic programming using pair algebras
BMC Bioinformatics, 2005 Background Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error
Giegerich Robert, Steffen Peter
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A NONLINEAR PROGRAMMING METHOD FOR DYNAMIC PROGRAMMING [PDF]
Macroeconomic Dynamics, 2016 A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient ...
Cai, Yongyang +4 more
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Stochastic Integer Programming by Dynamic Programming [PDF]
Statistica Neerlandica, 1985 AbstractStochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions.
B.J. Lageweg +4 more
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International Journal of Mathematics and Mathematical Sciences, 1988 This paper suggests a method of formulating any nonlinear integer programming problem, with any number of constraints, as an equivalent single constraint problem, thus reducing the dimensionality of the associated dynamic programming problem.
Balasubramanian Ram, A. J. G. Babu
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Study on Supervised Learning Model for Optimal Histogram Solution [PDF]
Jisuanji kexue, 2023 The dynamic programming binning algorithm is currently used to realize the optimal histogram.However,its time complexity is too high.A supervised learning model based on ProbSparse self-attention is proposed in this paper to learn the dynamic programming
CHEN Yunliang, LIU Hao, ZHU Guishui, HUANG Xiaohui, CHEN Xiaodao, WANG Lizhe
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