Multistage decisions and risk in Markov decision processes: towards effective approximate dynamic programming architectures
The scientific domain of this thesis is optimization under uncertainty for discrete event stochastic systems. In particular, this thesis focuses on the practical implementation of the Dynamic Programming (DP) methodology to discrete event stochastic systems. Unfortunately DP in its crude form suffer...
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Georgia Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1853/31654 |