Адаптивне керування славкокерованими марковськими та напівмарковськими моделями в дискретному часі
A Bayesian approach to Markov decision process problem [1] under stochastic uncertainty, when unknown transition probabilities are weakly disturbed with disturbances dependent on a decision strategy only is investigated. Observed decision process is assumed to be stationary in discrete time with fin...
Збережено в:
| Дата: | 2019 |
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| Автор: | |
| Формат: | Стаття |
| Мова: | Ukrainian |
| Опубліковано: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2019
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| Онлайн доступ: | http://journal.iasa.kpi.ua/article/view/174306 |
| Теги: |
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| Назва журналу: | System research and information technologies |
Репозитарії
System research and information technologies| Резюме: | A Bayesian approach to Markov decision process problem [1] under stochastic uncertainty, when unknown transition probabilities are weakly disturbed with disturbances dependent on a decision strategy only is investigated. Observed decision process is assumed to be stationary in discrete time with finite, countable or measurable phase state is based on separation principle of assessment and optimization problems. |
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