Genetic algorithm methods for solving the best stationary policy of finite Markov decision processes

This paper describes a heuristic approach to solving the optimal stationary policy of the standard finite Markov decision processes (MDP). For a MDP problem, there is a so-called policy-improvement algorithm, which can be used to determine optimal policies. It starts at an arbitrary policy f/sub 0/...

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Bibliographische Detailangaben

Hauptverfasser:	Chin, H.H., Jafari, A.A.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithm design and analysis Biology computing Communication networks Context modeling Evolution (biology) Genetic algorithms Optimal control Optimization methods Stochastic processes
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