Gnecco, Giorgio and Sanguineti, Marcello and Zoppoli, Riccardo
Exploiting Structural Results in Approximate Dynamic Programming.
In: EURO XXII, 8-11 July 2007, Prague, Czech Republic
p. 159.
(2007)
Full text not available from this repository.
Abstract
Efforts to cope with the curse of dimensionality in Dynamic Programming (DP) follow two main directions: i) problem simplification by simpler models and ii) use of smart approximators for the cost-to-go and/or policy functions. Here we focus on ii). We consider: a) structural properties of the cost-to-go and/or policy functions (to restrict approximation to certain function classes and to chose the approximators); b) suitable norms of the approximation error (to estimate how it propagates through stages). These ingredients can be combined to develop efficient approximate
DP algorithms.
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