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• W2214460044 abstract "Computing optimal control policies for the stochastic nonlinear systems associated with population dynamics is computationally and mathematically difficult. We discuss the characteristics of population management problems arising in forestry, fisheries and pest management and how these characteristics affect the selection of optimal control algorithms and the associated computations. We compare the advantages and disadvantages of differential dynamic programming and stochastic dynamic programming The computational issues associated with linear or nonlinear interpolation for stochastic dynamic programming are discussed. We conclude that for very large-scale nonlinear problems like those arising in forestry, differential dynamic programming would seem to be the most effective method. Most pest control problems require stochastic dynamic programming and nonlinear interpolation. Because of the high degree of parameter uncertainty for fisheries models, these problems require a stochastic procedure like dynamic programming, but in many cases linear interpolation will be adequate.KeywordsReservoir OperationSpline ApproximationComputational AdvantageStochastic Dynamic ProgrammingStochastic Nonlinear SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
• W2214460044 created "2016-06-24" @default.
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• W2214460044 date "1989-01-01" @default.
• W2214460044 modified "2023-09-27" @default.
• W2214460044 title "Stochastic Nonlinear Optimal Control of Populations: Computational Difficulties and Possible Solutions" @default.
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• W2214460044 doi "https://doi.org/10.1007/978-3-642-46693-9_6" @default.
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