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	Provedor de dados AgEcon (2) Autor Bond, Craig A. (2) Loomis, John B. (1) Palavra-chave Adaptive control (2) Adaptive management (2) Dynamic programming (2) Resource /Energy Economics and Policy (2) Value of experimentation (2) Value of information (2) Decisions under uncertainty (1) Learning (1) Nonpoint source pollution (1) Mais... Tipo do documento Working or Discussion Paper (2) Ano 2008 (2) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última On the Potential Use of Adaptive Control Methods for Improving Adaptive Natural Resource Management AgEcon Bond, Craig A.. The paradigm of adaptive natural resource management (AM), in which experiments are used to learn about uncertain aspects of natural systems, is gaining prominence as the preferred technique for administration of large-scale environmental projects. To date, however, tools consistent with economic theory have yet to be used to either evaluate AM strategies or improve decision-making in this framework. Adaptive control (AC) techniques provide such an opportunity. This paper demonstrates the conceptual link between AC methods, the alternative treatment of realized information during a planning horizon, and AM practices; shows how the different assumptions about the treatment of observational information can be represented through alternative dynamic... Tipo: Working or Discussion Paper Palavras-chave: Adaptive control; Adaptive management; Dynamic programming; Value of experimentation; Value of information; Resource /Energy Economics and Policy. Ano: 2008 URL: http://purl.umn.edu/108721 Using Numerical Dynamic Programming to Compare Passive and Active Learning in the Adaptive Management of Nutrients in Shallow Lakes AgEcon Bond, Craig A.; Loomis, John B.. This paper illustrates the use of dual/adaptive control methods to compare passive and active adaptive management decisions in the context of an ecosystem with a threshold effect. Using discrete-time dynamic programming techniques, we model optimal phosphorus loadings under both uncertainty about natural loadings and uncertainty regarding the critical level of phosphorus concentrations beyond which nutrient recycling begins. Active management is modeled by including the anticipated value of information (or learning) in the structure of the problem, and thus the agent can perturb the system (experiment), update beliefs, and learn about the uncertain parameter. Using this formulation, we define and value optimal experimentation both ex ante and ex post. Our... Tipo: Working or Discussion Paper Palavras-chave: Adaptive control; Adaptive management; Dynamic programming; Value of experimentation; Value of information; Nonpoint source pollution; Learning; Decisions under uncertainty; Resource /Energy Economics and Policy. Ano: 2008 URL: http://purl.umn.edu/108720 Registros recuperados: 2 Primeira ... 1 ... Última

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