Markov Decision Processes With Their Applications
Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs,...
محفوظ في:
| المؤلفون الرئيسيون: | , |
|---|---|
| التنسيق: | Livre numérique |
| اللغة: | Anglais |
| منشور في: |
New York, NY :
Springer US
2008.
Cham : Springer Nature |
| سلاسل: | Advances in Mechanics and Mathematics
14 |
| الموضوعات: | |
| الوصول للمادة أونلاين: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| ملاحظة: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Markov Decision Processes With Their Applications, Texte imprimé, 9780387369501 • Markov Decision Processes with Their Applications, Texte imprimé, 9780387515465 • Markov Decision Processes with Their Applications, Texte imprimé, 9781441942388 |
جدول المحتويات:
- Discretetimemarkovdecisionprocesses: Total Reward
- Discretetimemarkovdecisionprocesses: Average Criterion
- Continuous Time Markov Decision Processes
- Semi-Markov Decision Processes
- Markovdecisionprocessesinsemi-Markov Environments
- Optimal control of discrete event systems: I
- Optimal control of discrete event systems: II
- Optimal replacement under stochastic Environments
- Optimalal location in sequential online Auctions.