Results 1 to 10 of about 50 (44)
Resilient Dynamic Programming [PDF]
Algorithmica, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
CAMINITI, SAVERIO +3 more
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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).
Haskell, William B. +2 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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Linear programming and dynamics [PDF]
Ural mathematical journal, 2015 Summary: In a Hilbert space we consider the linear boundary value problem of optimal control based on the linear dynamics and the terminal linear programming problem at the right end of the time interval. There is provided a saddle-point method to solve it. Convergence of the method is proved.
Antipin, A. S., Khoroshilova, E. V.
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Dynamic Policy Programming [PDF]
, 2010 Submitted to Journal of Machine Learning ...
Gheshlaghi Azar, M. +2 more
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DISCRETE DYNAMIC PROGRAMMING [PDF]
The Annals of Mathematical Statistics, 1962 We consider a system with a finite number $S$ of states $s$, labeled by the integers $1, 2, \cdots, S$. Periodically, say once a day, we observe the current state of the system, and then choose an action $a$ from a finite set $A$ of possible actions. As a joint result of the current state $s$ and the chosen action $a$, two things happen: (1) we receive
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A NONLINEAR PROGRAMMING METHOD FOR DYNAMIC PROGRAMMING [PDF]
Macroeconomic Dynamics, 2013 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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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.
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Dynamic Ic and Dynamic Programming [PDF]
SSRN Electronic Journal, 2019 This paper develops a dynamic programming method when the one-stage deviation principle in the sense of mechanism design literature doesn’t hold. The commonly used dynamic programming method is valid only if the one-stage deviation principle in the sense of mechanism design literature is satisfied; it doesn't hold in every model, and the one-stage ...
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Physical Review Letters32 pages; stronger results than v1, with significant rewriting of the main ...
Jeongrak Son +3 more
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