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Title:
compositional reasoning for markov decision processes
Author: Deng Yuxin ; Hennessy Matthew
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference Name: 4th IPM International Conference on Fundamentals of Software Engineering, FSEN 2011
Conference Date: April 20, 2011 - April 22, 2011
Issued Date: 2012
Conference Place: Tehran, Iran
Keyword: Markov processes
Indexed Type: EI
ISSN: 0302-9743
ISBN: 9783642293191
Department: (1) Dept. Comp. Sci. and Eng. MOE-Microsoft Key Lab. for Intell. Comp. and Syst. Shanghai Jiao Tong University China; (2) State Key Lab. of Comp. Sci. Inst. of Software Chinese Academy of Sciences China; (3) Trinity College Dublin Ireland
Abstract: Markov decision processes (MDPs) have long been used to model qualitative aspects of systems in the presence of uncertainty. However, much of the literature on MDPs takes a monolithic approach, by modelling a system as a particular MDP; properties of the system are then inferred by analysis of that particular MDP. In this paper we develop compositional methods for reasoning about the qualitative behaviour of MDPs. We consider a class of labelled MDPs called weighted MDPs from a process algebraic point of view. For these we define a coinductive simulation-based behavioural preorder which is compositional in the sense that it is preserved by structural operators for constructing MDPs from components. For finitary convergent processes, which are finite-state and finitely branching systems without divergence, we provide two characterisations of the behavioural preorder. The first uses a novel qualitative probabilistic logic, while the second is in terms of a novel form of testing, in which benefits are accrued during the execution of tests. © 2012 Springer-Verlag.
English Abstract: Markov decision processes (MDPs) have long been used to model qualitative aspects of systems in the presence of uncertainty. However, much of the literature on MDPs takes a monolithic approach, by modelling a system as a particular MDP; properties of the system are then inferred by analysis of that particular MDP. In this paper we develop compositional methods for reasoning about the qualitative behaviour of MDPs. We consider a class of labelled MDPs called weighted MDPs from a process algebraic point of view. For these we define a coinductive simulation-based behavioural preorder which is compositional in the sense that it is preserved by structural operators for constructing MDPs from components. For finitary convergent processes, which are finite-state and finitely branching systems without divergence, we provide two characterisations of the behavioural preorder. The first uses a novel qualitative probabilistic logic, while the second is in terms of a novel form of testing, in which benefits are accrued during the execution of tests. © 2012 Springer-Verlag.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15683
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Deng Yuxin,Hennessy Matthew. compositional reasoning for markov decision processes[C]. 见:4th IPM International Conference on Fundamentals of Software Engineering, FSEN 2011. Tehran, Iran. April 20, 2011 - April 22, 2011.
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