Verification of general Markov decision processes by approximate similarity relations and policy refinement
In this work we introduce new approximate similarity relations that are shown to be key for policy (or control) synthesis over general Markov decision processes. The models of interest are discrete-time Markov decision processes, endowed with uncountably infinite state spaces and metric output (or o...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Society for Industrial and Applied Mathematics
2017
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