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Partially Observable Markov Decision Process: Artificial Intelligence, Automated Planning, Markov Decision Process
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(Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!
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| Please note that the content of this book primarily consists of articles
available from Wikipedia or other free sources online. A Partially
Observable Markov Decision Process (POMDP) is a generalization of a
Markov Decision Process. A POMDP models an agent decision process in
which it is assumed that the system dynamics are determined by an MDP,
but the agent cannot directly observe the underlying state. Instead, it
must maintain a probability distribution over the set of possible
states, based on a set of observations and observation probabilities,
and the underlying MDP. The POMDP framework is general enough to model a
variety of real-world sequential decision processes. Applications
include robot navigation problems, machine maintenance, and planning
under uncertainty in general. The framework originated in the Operations
Research community, and was later taken over by the Artificial
Intelligence and Automated Planning communities. |
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i.d.R. innert 7-14 Tagen versandfertig
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