Convex Optimization for Parameter Synthesis in MDPs

Probabilistic model-checking aims to prove whether a Markov decision process (MDP) satisfies a temporal logic specification. The underlying methods rely on an often unrealistic assumption that the MDP is precisely known. Consequently, parametric MDPs (pMDPs) extend MDPs with transition probabilities...

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Vydané v:	IEEE transactions on automatic control Ročník 67; číslo 12; s. 6333 - 6348
Hlavní autori:	Cubuktepe, Murat, Jansen, Nils, Junges, Sebastian, Katoen, Joost-Pieter, Topcu, Ufuk
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.12.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation models Collision avoidance Computational geometry Convex analysis Convex functions Convex optimization Convexity Markov processes Mathematical programming Model checking Optimization Parameters Probabilistic logic Probabilistic models Quadratic programming Scalability Specifications Synthesis Temporal logic Transition probabilities
ISSN:	0018-9286, 1558-2523
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