Symblicit algorithms for optimal strategy synthesis in monotonic Markov decision processes
When treating Markov decision processes (MDPs) with large state spaces, using explicit representations quickly becomes unfeasible. Lately, Wimmer et al. have proposed a so-called symblicit algorithm for the synthesis of optimal strategies in MDPs, in the quantitative setting of expected mean-payoff....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Open Publishing Association
2014-07-01
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| Series: | Electronic Proceedings in Theoretical Computer Science |
| Online Access: | http://arxiv.org/pdf/1407.5396v1 |