Haut PDF On Submodular Value Functions of Dynamic Programming
On Submodular Value Functions of Dynamic Programming
... Unite´ de recherche INRIA Lorraine, Technopoˆle de Nancy-Brabois, Campus scientifique, 615 rue du Jardin Botanique, BP 101, 54600 VILLERS LE` S NANCY Unite´ de recherche INRIA Rennes, Ir[r] ...
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On Aggregators and Dynamic Programming
... existence of a solution to the Bellman ...possibility of identifying a pair of functions v and v which fullfils the assumptions of this ...class of examples is useful as it ...
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Dynamic programming for optimal control of stochastic McKean-Vlasov dynamics
... continuity of the value function in the Wasserstein space of probability measures, we are able to prove a dynamic programming principle (DPP) for our stochastic McKean-Vlasov control ...
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Dynamic programming approach to principal-agent problems
... contribution of our paper is the following: we provide a systematic method to solve any problem of this sort, including those in which Agent can also control the volatility of the output process, and ...
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Approximate dynamic programming with a fuzzy parameterization
... approximate dynamic programming, fuzzy approximation, value iteration, convergence ...Introduction Dynamic programming (DP) is a powerful paradigm for solving optimal control problems, ...
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Value function for regional control problems via dynamic programming and Pontryagin maximum principle
... regions of the state space and present discontinuities at their ...number of switchings (no Zeno phenomenon), we use the duplication technique to show that the value function of the regional ...
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Approximating Submodular Functions Everywhere
... ular functions motivates us to investigate other fun- damental questions concerning their ...a submodular func- tion? How much of that information can be obtained in just a few value oracle ...
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Allowing non-submodular score functions in distributed task allocation
... in value because of the presence of other assign- ...score functions typically used in task allocation satisfy this submodularity condition (for example the information theory community [10]), ...
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Metric Learning with Submodular Functions
... Accuracy of KNN with different metrics learning algorithm and their running time in ...ξ of the ξ-additive varies from 1 to min(10, m). A value of ξ = 1 means that there is no interaction be- ...
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An approximate dynamic programming approach to solving dynamic oligopoly models
... use of this approximation architecture makes the linear program in Algorithm 3 a tractable ...millions of billions states only thousands of basis functions are ...selection of basis ...
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Air-Combat Strategy Using Approximate Dynamic Programming
... many of the dangerous missions currently flown by manned ...complexity of some tasks, such as air combat, have precluded UAS from successfully carrying out these missions ...formulation of a level ...
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A CMOS Current-Mode Dynamic Programming Circuit
... notion of “curse of dimensionality” as coined by Bellman in [10] refers to the vast computational effort required for the numerical solution of Bellman’s equation when there is a large number ...
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Branch-and bound strategies for dynamic programming
... in the state space Q in low-speed (tape, disk) computer storage. It is common knowledge that in real problems excessive high-speed storage requirements.. can present a serious implementa[r] ...
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Branch-and-bound strategies for dynamic programming
... Let ^ be an upper bound on the objective function value of any optimal solution to the original discrete optimization problem 9, Then, since .^ is a representation of 9.. it follows that[r] ...
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Dynamic Programming for Mean-Field Type Control
... extension of the HJB dynamic programming ...well-posedness of the HJB or adjoint equation because it is set in an infinite domain in ...lack of proof of convergence of the ...
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Optimal routing configuration clustering through dynamic programming
... sequence of traffic matrices (TMs), which might represent the evolution over time of end-to-end connections ...clusters of contiguous TMs with a single routing configuration applied to each ...TMs ...
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Local minimization algorithms for dynamic programming equations
... set of elements of U (see for instance [1, 12, 17] and references ...contribution of this paper is to demonstrate that an accurate realization of the min-operation on the right hand side ...
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Risk-aware decision making and dynamic programming
... π of the ...space of the agent. The random selection of an action in A according to a distribution conditioned on the information state i t ∈ I is ...
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Adaptive aggregation methods for discounted dynamic programming
... (The smoothing of the error after a single successive approximation step in this example is a coincidence. In general, several successive approximation steps will be requir[r] ...
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Dynamic Programming for Mean-field type Control
... variation of J with respect to u we have used 100 iterations of a gradient method with fixed step size, ω = ...parameters of the problem are T = 2, h = ...method of degree 1 on a mesh ...
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