Filters








19,475 Hits in 6.2 sec

Equivalence and Minimization for Model Checking Labeled Markov Chains

Peter Buchholz, Jan Kriege, Dimitri Scheftelowitsch
2016 Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools  
Model checking of Markov chains using logics like CSL or asCSL proves whether a logical formula holds for a state of the Markov chain.  ...  In this paper, model checking is extended to prove formulas for distributions rather than single states.  ...  EQUIVALENCE OF LABELED MARKOV CHAINS We first define equivalence of CTLMCs as a natural adoption of trace equivalence for labeled Markov processes [13] . Definition 2.  ... 
doi:10.4108/eai.14-12-2015.2262622 dblp:journals/sis/BuchholzKS16 fatcat:tmplwxkn4vbr7awvgszx6ojgni

Using Stochastic Comparison for Efficient Model Checking of Uncertain Markov Chains

Serge Haddad, Nihal Pekergin
2009 2009 Sixth International Conference on the Quantitative Evaluation of Systems  
We consider model checking of Discrete Time Markov Chains (DTMC) with transition probabilities which are not exactly known but lie in a given interval.  ...  Model checking a Probabilistic Computation Tree Logic (PCTL) formula for interval-valued DTMCs (IMC) has been shown to be NP hard and co-NP hard.  ...  The model checking of interval valued Markov chains has been investigated in [23] .  ... 
doi:10.1109/qest.2009.42 dblp:conf/qest/HaddadP09 fatcat:vvqqnzhj65hnzfetqnaze5azsm

Ten Years of Performance Evaluation for Concurrent Systems Using CADP [chapter]

Nicolas Coste, Hubert Garavel, Holger Hermanns, Frédéric Lang, Radu Mateescu, Wendelin Serwe
2010 Lecture Notes in Computer Science  
Traditional performance models like Markov chains and queueing networks are not easy to apply for large-sized systems, mainly because they lack hierarchical composition and abstraction means.  ...  The design of models suited for performance and reliability analysis is challenging due to complexity and size of the modeled systems, in particular for those with a high degree of irregularity.  ...  The Interactive Markov Chain Model An Imc (Interactive Markov Chain) [3] is a state-transition graph with a denumerable state space, action-labeled transitions, as well as stochastic transitions (also  ... 
doi:10.1007/978-3-642-16561-0_18 fatcat:eenulhij7rfe7djagjri4cpaju

Prediction and generation of binary Markov processes: Can a finite-state fox catch a Markov mouse?

Joshua B. Ruebeck, Ryan G. James, John R. Mahoney, James P. Crutchfield
2018 Chaos  
We show that a previously proposed generator for a particular set of binary Markov processes is, in fact, not minimal.  ...  Our results shed the first quantitative light on the relative (minimal) costs of prediction and generation.  ...  Army Research Laboratory and the U. S. Army Research Office under contracts W911NF-13-1-0390 and W911NF-13-1-0340. JR was funded by the 2016 NSF Research Experience for Undergraduates program.  ... 
doi:10.1063/1.5003041 pmid:29390624 fatcat:vgwkyy4z6jb37pbkighycoslbu

On Block Ordering of Variables in Graphical Modelling

ALBERTO ROVERATO, LUCA LA ROCCA
2006 Scandinavian Journal of Statistics  
Structural learning within a family of B-consistent chain graphs requires to deal with Markov equivalence.  ...  We provide a graphical characterisation of equivalence classes of B-consistent chain graphs, namely the B-essential graphs, as well as a procedure to construct the B-essential graph for any given equivalence  ...  Acknowledgements The authors wish to thank Davide Cavallini for useful comments. Part of this paper was written when the first author was visiting the Center for Genomic Regulation, University  ... 
doi:10.1111/j.1467-9469.2006.00478.x fatcat:dzzgovre6vc5zmfo2wjheezxji

The Ins and Outs of the Probabilistic Model Checker MRMC

Joost-Pieter Katoen, Ivan S. Zapree, Ernst Moritz Hahn, Holger Hermanns, David N. Jansen
2009 2009 Sixth International Conference on the Quantitative Evaluation of Systems  
The Markov Reward Model Checker (MRMC) is a software tool for verifying properties over probabilistic models. It supports PCTL and CSL model checking, and their reward extensions.  ...  Recent tool features include time-bounded reachability analysis for uniform CTMDPs and CSL model checking by discrete-event simulation.  ...  We thank Maneesh Khattri (Oxford Univ.), Christina Jansen (RWTH Aachen), and Tim Kemna (Univ. Twente) for their implementation efforts.  ... 
doi:10.1109/qest.2009.11 dblp:conf/qest/KatoenZHHJ09 fatcat:c2ziyci6xjcyrlq253ltcitafi

The ins and outs of the probabilistic model checker MRMC

Joost-Pieter Katoen, Ivan S. Zapreev, Ernst Moritz Hahn, Holger Hermanns, David N. Jansen
2011 Performance evaluation (Print)  
The Markov Reward Model Checker (MRMC) is a software tool for verifying properties over probabilistic models. It supports PCTL and CSL model checking, and their reward extensions.  ...  Recent tool features include time-bounded reachability analysis for uniform CTMDPs and CSL model checking by discrete-event simulation.  ...  We thank Maneesh Khattri (Oxford Univ.), Christina Jansen (RWTH Aachen), and Tim Kemna (Univ. Twente) for their implementation efforts.  ... 
doi:10.1016/j.peva.2010.04.001 fatcat:mxrwjxdez5c2ropa5wczhxo4oa

EQUIVALENCE OF LABELED MARKOV CHAINS

LAURENT DOYEN, THOMAS A. HENZINGER, JEAN-FRANÇOIS RASKIN
2008 International Journal of Foundations of Computer Science  
We consider the equivalence problem for labeled Markov chains (LMCs), where each state is labeled with an observation.  ...  Then, we consider the equivalence problem for labeled Markov decision processes (LMDPs), which asks given two LMDPs whether for every scheduler (i.e. way of resolving the nondeterministic decisions) for  ...  This shows that the algorithms for equivalence of probabilistic automata can also be used for checking equivalence of labeled Markov chains with the same complexity.  ... 
doi:10.1142/s0129054108005814 fatcat:m3cf7rxsnrdclb63vhrhzr47au

On the metric-based approximate minimization of Markov Chains

Giovanni Bacci, Giorgio Bacci, Kim G. Larsen, Radu Mardare
2018 Journal of Logical and Algebraic Methods in Programming  
In this paper, we address the approximate minimization problem of Markov Chains (MCs) from a behavioral metric-based perspective.  ...  Specifically, given a finite MC and a positive integer k, we are looking for an MC with at most k states having minimal distance to the original.  ...  However, by arguments analogous to [11, 14] and leveraging on the ideas that made us produce the MC in Example 10, we suspect that BA-λ is hard for the square-root-sum problem.  ... 
doi:10.1016/j.jlamp.2018.05.006 fatcat:e5pmxipucvfhxjs3h2j5khcyom

An Introduction to Quantum Model Checking

Andrea Turrini
2022 Applied Sciences  
In this paper, we will consider the problem of model checking quantum systems and present the solutions given in literature for solving such a problem with respect to different types of properties.  ...  Model checking is a well-established and widely adopted framework used to verify whether a given system satisfies the desired properties.  ...  By operating on this larger Hilbert space, we have the information we need to solve the model checking problem for ω-regular properties for labelled quantum Markov chains.  ... 
doi:10.3390/app12042016 fatcat:s6fiur3alnd3toa3mwcatbe6au

Mungojerrie: Reinforcement Learning of Linear-Time Objectives [article]

Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, Dominik Wojtczak
2021 arXiv   pre-print
Mungojerrie (https://plv.colorado.edu/mungojerrie/) is a tool for testing reward schemes for ω-regular objectives on finite models.  ...  The tool contains reinforcement learning algorithms and a probabilistic model checker. Mungojerrie supports models specified in PRISM and ω-automata specified in HOA.  ...  For model checking and reinforcement learning, this nondeterminism must be resolved on the fly.  ... 
arXiv:2106.09161v2 fatcat:k7jvqed2wzebfbthfg2zwhxzo4

Model Checking of Open Interval Markov Chains [chapter]

Souymodip Chakraborty, Joost-Pieter Katoen
2015 Lecture Notes in Computer Science  
We consider the model checking problem for interval Markov chains with open intervals.  ...  We show that, as far as model checking (and reachability) is concerned, open intervals does not cause any problem, and with minor modification existing algorithms can be used for model checking interval  ...  The authors thank Hongfei Fu for discussions on the topic of this paper.  ... 
doi:10.1007/978-3-319-18579-8_3 fatcat:w6aaj6fsvvcbzklbmvowb53vve

Least upper bounds for probability measures and their applications to abstractions

Rohit Chadha, Mahesh Viswanathan, Ramesh Viswanathan
2014 Information and Computation  
In this paper we present new ways to abstract Discrete Time Markov Chains (DTMCs), Markov Decision Processes (MDPs), and Continuous Time Markov Chains (CTMCs).  ...  Abstraction is a key technique to combat the state space explosion problem in model checking probabilistic systems.  ...  In this paper, we present new methods to abstract probabilistic systems modeled by Discrete Time Markov Chains (DTMC), Markov Decision Processes (MDP), and Continuous Time Markov Chains (CTMC).  ... 
doi:10.1016/j.ic.2013.12.003 fatcat:yvssuuze35bhjhhz5u32jszejm

Least Upper Bounds for Probability Measures and Their Applications to Abstractions [chapter]

Rohit Chadha, Mahesh Viswanathan, Ramesh Viswanathan
2008 Lecture Notes in Computer Science  
In this paper we present new ways to abstract Discrete Time Markov Chains (DTMCs), Markov Decision Processes (MDPs), and Continuous Time Markov Chains (CTMCs).  ...  Abstraction is a key technique to combat the state space explosion problem in model checking probabilistic systems.  ...  In this paper, we present new methods to abstract probabilistic systems modeled by Discrete Time Markov Chains (DTMC), Markov Decision Processes (MDP), and Continuous Time Markov Chains (CTMC).  ... 
doi:10.1007/978-3-540-85361-9_23 fatcat:lhwghcgjejhejafoxnvrp365hy

Reachability in parametric Interval Markov Chains using constraints

Anicet Bart, Benoît Delahaye, Paulin Fournier, Didier Lime, Éric Monfroy, Charlotte Truchet
2018 Theoretical Computer Science  
In this work, we study the difference between pIMCs and other Markov Chain abstractions models and investigate the two usual semantics for IMCs: once-and-for-all and at-every-step.  ...  Parametric Interval Markov Chains (pIMCs) are a specification formalism that extend Markov Chains (MCs) and Interval Markov Chains (IMCs) by taking into account imprecision in the transition probability  ...  Definition 1 (Markov chain Abstraction Model). A Markov chain abstraction model (an abstraction model for short) is a pair (L, |=) where L is a nonempty set and |= is a relation between MC and L.  ... 
doi:10.1016/j.tcs.2018.06.016 fatcat:7tlcirehbzbihccomofo4joobu
« Previous Showing results 1 — 15 out of 19,475 results