Examines several fundamentals concerning the manner in which Markov
decision problems may be properly formulated and the determination
of solutions or their properties. Coverage includes optimal
equations, algorithms and their characteristics, probability
distributions, modern development in the Markov decision process
area, namely structural policy analysis, approximation modeling,
multiple objectives and Markov games. Copiously illustrated with
examples.
General
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