- Know basic notions of Markov-Chain with a discrete and continuous time
- Investigate the properties of Markov-Chains with rewards
- Derive iterative solution for Markov sequential decision processes
- Develop the policy-iteration for the solution of optimization problems
- Apply the policy-iteration algorithm to real-life control problems
- Understand the main properties of the sequential decision processes with discounting
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Calculation of the state probabilities of Markov processes, algorithms of dynamic programming, solution of the optimization problem with the help of Markov decision processes
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