<p>Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision Processes (MDPs) and their applications. Each chapter was written by a leading expert in the reΒ spective area. The papers cover major research areas and methodologies, and discuss open questions and future resea
Handbook of Markov Decision Processes: Methods and Applications
β Scribed by Eugene A. Feinberg, Adam Shwartz (eds.)
- Publisher
- Springer
- Year
- 2002,2012
- Tongue
- English
- Leaves
- 557
- Edition
- reprint
- Category
- Library
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<p><P>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 po
<p><P>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
<p><P>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