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Title:
Model repair for Markov decision processes
Author: Chen, Taolue (1) ; Hahn, Ernst Moritz (1) ; Han, Tingting (1) ; Kwiatkowska, Marta (1) ; Qu, Hongyang (2) ; Zhang, Lijun (3)
Conference Name: 2013 International Symposium on Theoretical Aspects of Software Engineering, TASE 2013
Conference Date: July 1, 2013 - July 3, 2013
Issued Date: 2013
Conference Place: Birmingham, United kingdom
Publish Place: IEEE Computer Society, 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States
Indexed Type: EI
ISBN: 9780768550534
Department: (1) Department of Computer Science, University of Oxford, United Kingdom; (2) Department of Automatic Control and Systems Engineering, University of Sheffield, United Kingdom; (3) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, China
Abstract: Markov decision processes (MDPs) are often used for modelling distributed systems with probabilistic failure or randomisation. We consider the problem of model repair for MDPs defined as follows: if the MDP fails to satisfy a property, we aim to find new values for the transition probabilities so that the property is guaranteed to hold, while at the same time the cost of repair is minimised. Because solving the MDP repair problem exactly is infeasible, in this paper we focus on approximate solution methods. We first formulate a region-based approach, which yields an interval in which the minimal repair cost is contained. As an alternative, we also consider sampling based approaches, which are faster but unable to provide lower bounds on the repair cost. We have integrated both methods into the probabilistic model checker PRISM and demonstrated their usefulness in practice using a computer virus case study. © 2013 IEEE.
English Abstract: Markov decision processes (MDPs) are often used for modelling distributed systems with probabilistic failure or randomisation. We consider the problem of model repair for MDPs defined as follows: if the MDP fails to satisfy a property, we aim to find new values for the transition probabilities so that the property is guaranteed to hold, while at the same time the cost of repair is minimised. Because solving the MDP repair problem exactly is infeasible, in this paper we focus on approximate solution methods. We first formulate a region-based approach, which yields an interval in which the minimal repair cost is contained. As an alternative, we also consider sampling based approaches, which are faster but unable to provide lower bounds on the repair cost. We have integrated both methods into the probabilistic model checker PRISM and demonstrated their usefulness in practice using a computer virus case study. © 2013 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16661
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Chen, Taolue ,Hahn, Ernst Moritz ,Han, Tingting ,et al. Model repair for Markov decision processes[C]. 见:2013 International Symposium on Theoretical Aspects of Software Engineering, TASE 2013. Birmingham, United kingdom. July 1, 2013 - July 3, 2013.
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