Continuous-Time Markov Decision Processes Theory and Applications
Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populati...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2009, 2009
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| Edition: | 1st ed. 2009 |
| Series: | Stochastic Modelling and Applied Probability
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- and Summary
- Continuous-Time Markov Decision Processes
- Average Optimality for Finite Models
- Discount Optimality for Nonnegative Costs
- Average Optimality for Nonnegative Costs
- Discount Optimality for Unbounded Rewards
- Average Optimality for Unbounded Rewards
- Average Optimality for Pathwise Rewards
- Advanced Optimality Criteria
- Variance Minimization
- Constrained Optimality for Discount Criteria
- Constrained Optimality for Average Criteria