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- W284868800 abstract "This chapter describes dynamic programming as an extremely flexible optimization technique. The variety of problems that have been formulated as dynamic programs seems endless, accounting for the frequent use of dynamic programming as a conceptual and analytical tool. Its application to solving problems has been limited by the computational difficulties, which arise when the number of possible states is large. According to Bellman, the explosive increase in the computing time and computer storage requirements for state spaces of high dimension is called the curse of dimensionality. This presents an obstacle to the widespread application of dynamic programming because representative models of real systems require multidimensional state spaces. An approach to this problem is to search for efficient heuristics. In multi-sector growth models, the status of an economy is represented by a state vector whose components indicate the current stock levels of the various goods; the goal is to control the economy over time so as to maximize some objective function subject to constraints imposed by factors such as technology and resource availability." @default.
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- W284868800 date "1978-01-01" @default.
- W284868800 modified "2023-09-27" @default.
- W284868800 title "STEADY-STATE POLICIES, DYNAMIC PROGRAMMING, AND OPTIMAL ECONOMIC GROWTH" @default.
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- W284868800 doi "https://doi.org/10.1016/b978-0-12-568150-6.50014-3" @default.
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