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A Stochastic Hybrid Systems framework for analysis of Markov reward models

S.V. Dhople, L. DeVille, A.D. Domínguez-García
2014 Reliability Engineering & System Safety  
Send comment regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services.  ...  Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. 239-18 298-102 REPORT DOCUMENTATION PAGE Form Approved OMB NO. 0704-0188 Public reporting burden for this collection of information is estimated to  ...  In this paper, we propose a framework that enables the formulation of very general reward models, and unies the analysis of a variety of previously studied Markov reward models.  ... 
doi:10.1016/j.ress.2013.10.011 fatcat:yz4ehly2djakxdykymimy6bs5y

Stochastic Reachability: From Markov Chains to Stochastic Hybrid Systems

Manuela L. Bujorianu
2011 IFAC Proceedings Volumes  
Stochastic reachability analysis is a key factor in the verification and deployment of stochastic hybrid systems.  ...  ) of stochastic hybrid systems.  ...  Hybrid Processes Stochastic Analysis Elements: For the analysis of SHS, we need to make use of the different characterizations of Markov processes.  ... 
doi:10.3182/20110828-6-it-1002.03148 fatcat:hznsoxcl6vgo7guayhcbcq54ne

Sirio: A Framework for Simulation and Symbolic State Space Analysis of non-Markovian Models

Laura Carnevali, Lorenzo Ridi, Enrico Vicario
2011 2011 Eighth International Conference on Quantitative Evaluation of SysTems  
Sirio is a framework for simulation and symbolic analysis of preemptive and stochastic extensions of Time Petri Nets (TPNs), enabling an integrated approach to correctness verification and quantitative  ...  As a characterizing trait, Sirio manages models with multiple concurrently enabled generally distributed (GEN) timers that underlie a Generalized Semi-Markov Process (GSMP).  ...  Abstract-Sirio is a framework for simulation and symbolic analysis of preemptive and stochastic extensions of Time Petri Nets (TPNs), enabling an integrated approach to correctness verification and quantitative  ... 
doi:10.1109/qest.2011.29 dblp:conf/qest/CarnevaliRV11 fatcat:ocbcvsbkebftfctihkar2bvrra

Page 9478 of Mathematical Reviews Vol. , Issue 2001M [page]

2001 Mathematical Reviews  
This paper proposes a simulation-based algorithm for optimizing the average reward in a finite-state Markov reward process that depends on a set of parameters.  ...  The authors study a Gauss-Markov model as a test case, because it allows for explicit computation. Given some particle system method, let x?  ... 

A Framework for Simulation and Symbolic State Space Analysis of Non-Markovian Models [chapter]

Laura Carnevali, Lorenzo Ridi, Enrico Vicario
2011 Lecture Notes in Computer Science  
Sirio is a framework for simulation and analysis of various timed extensions of Petri Nets, supporting correctness verification and quantitative evaluation of timed concurrent systems.  ...  As a characterizing trait, Sirio is expressly designed to support reuse and to facilitate extensions such as the definition of new reward measures, new variants of the analysis, and new models with a different  ...  The OsMoSys Multi-solution Framework [34] comprises a SW environment for the analysis of multi-formalism models, which provides a strong separation between model representation and analysis algorithms  ... 
doi:10.1007/978-3-642-24270-0_30 fatcat:uffiwa43zzb3ljn4gfgffm64ne

Fuzzy interpretation for temporal-difference learning in anomaly detection problems

A.V. Sukhanov, S.M. Kovalev, V. Stýskala
2016 Bulletin of the Polish Academy of Sciences: Technical Sciences  
Presented approach is based on a hybridization of stochastic Markov reward model by using fuzzy production rules, which allow to correct Markov information based on expert knowledge about the process dynamics  ...  These systems are extensively implemented into dispatching control systems for railways, intrusion detection systems for computer security and other domains centered on big data analysis.  ...  One of the ways for this problems decision is the foundation of hybrid fuzzy-stochastic model by merging the above described Markov model with fuzzy production model mentioned in this paper.  ... 
doi:10.1515/bpasts-2016-0070 fatcat:k7bewhdmyndufmbu4cj6aihno4

From software verification to 'everyware' verification

Marta Kwiatkowska
2013 Computer Science - Research and Development  
The focus is on a advancing quantitative verification in new and previously unexplored directions, including game-based techniques, incorporation of continuous dynamics in addition to stochasticity, and  ...  Model-based design and verification techniques have proved useful in supporting the design process by detecting and correcting flaws in a number of ubiquitous computing applications, but are limited by  ...  The appropriate models in this context are variants of stochastic hybrid automata, e.g. [53] , but they are highly complex and the existing analysis methods are limited.  ... 
doi:10.1007/s00450-013-0249-1 fatcat:yijv5tfqwjb5rlopsnmy6gpsf4

New insights on stochastic reachability

Manuela L. Bujorianu, John Lygeros
2007 2007 46th IEEE Conference on Decision and Control  
In this paper, we give new characterizations of the stochastic reachability problem for stochastic hybrid systems in the language of different theories that can be employed in studying stochastic processes  ...  (Markov processes, potential theory, optimal control).  ...  For these systems, the researchers have introduced the modelling paradigm called stochastic hybrid systems (SHS) [4] .  ... 
doi:10.1109/cdc.2007.4434784 dblp:conf/cdc/BujorianuL07 fatcat:ksqrpbewkvbvrf27ccvixps2bm

How good are the stochastic analysis methods for stochastic reachability

Manuela L. Bujorianu
2011 IEEE Conference on Decision and Control and European Control Conference  
Stochastic reachability problem can be treated as an exit problem for a suitable class of Markov processes.  ...  For stochastic hybrid systems, safety verification methods are very little supported mainly because of complexity and difficulty of the associated mathematical problems.  ...  Hybrid Processes Stochastic Analysis Elements: For the analysis of stochastic hybrid systems, we need to use the different characterizations of Markov processes.  ... 
doi:10.1109/cdc.2011.6161349 dblp:conf/cdc/Bujorianu11 fatcat:gjbtud5hergyrgjo6dravagogu

A physics-informed reinforcement learning approach for the interfacial area transport in two-phase flow [article]

Zhuoran Dang, Mamoru Ishii
2020 arXiv   pre-print
A Markov Decision Process that describes the bubble transport is established by assuming that the development of two-phase flow is a stochastic process with Markov property.  ...  The case studies on the PIRLF performance also show that the type of reward function that is related to the physical model can affect the framework performance.  ...  As suggested by the original DDPG paper [2] , Adam optimizer [26] is applied for learning the parameters in the actor and critic neural networks with learning rates of 10 −4 and 10 −3 , respectively  ... 
arXiv:1908.02750v2 fatcat:a4alyxnw7feyhmsrwt6q7huzpu

Validation of cognitive models for collaborative hybrid systems with discrete human input

Abraham P. Vinod, Yuqing Tang, Meeko M. K. Oishi, Katia Sycara, Christian Lebiere, Michael Lewis
2016 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)  
We use reachability analysis to predict the outcome of the resulting discrete-time stochastic hybrid system, in which the outcome is defined as a function of the system trajectory.  ...  The novelty of this work is 1) a method to compute expected outcome in a hybrid dynamical system with a Markov chain model of the human's discrete choice, and 2) application of this method to validation  ...  In this paper, we use the framework of discrete-time stochastic hybrid systems to model human-in-the-loop cyberphysical systems [15] with discrete choice, and pose the question of expected outcome in  ... 
doi:10.1109/iros.2016.7759514 dblp:conf/iros/VinodTOSL016 fatcat:psssuqffnjgnfapwzjxd7kjghi

Quantitative Aspects of Programming Languages and Systems over the past 2^4 years and beyond

Alessandro Aldini
2020 Electronic Proceedings in Theoretical Computer Science  
Hence, they need to be integrated both at the level of system modeling and within the verification methodologies and tools.  ...  Along the last two decades a variety of theoretical achievements and automated techniques have contributed to make quantitative modeling and verification mainstream in the research community.  ...  [143] , stochastic extension of the hybrid process algebra HYPE [32, 33, 68] , stochastic extension of the Software Component Ensemble Language for modeling ensemble based autonomous systems [101]  ... 
doi:10.4204/eptcs.312.1 fatcat:4fjvygbppjbq3k5ury2kvue3nq

An Easy-to-Use, Efficient Tool-Chain to Analyze the Availability of Telecommunication Equipment [chapter]

Kai Lampka, Markus Siegle, Max Walter
2007 Lecture Notes in Computer Science  
In this paper, we introduce a tool chain where OpenSESAME is employed for specifying models of fault-tolerant systems, and at the back end our symbolic engine is employed for carrying out numerical Markov  ...  The tool OpenSESAME offers an easy-to-use modeling framework which enables realistic availability and reliability analysis of faulttolerant systems.  ...  In contrast, Markov Reward models (MRMs) provide a powerful mathematical framework for computing system state probabilities and thus quantifying a system under study.  ... 
doi:10.1007/978-3-540-70952-7_3 fatcat:k4zebbgaajd3jhriikxt3mqdfy

Stochastic Tools for Network Intrusion Detection [chapter]

Lu Yu, Richard R. Brooks
2018 Proceedings of International Symposium on Sensor Networks, Systems and Security  
The partially observable Markov decision process (POMDP) is a useful choice for controlling stochastic systems.  ...  As a combination of two Markov models, POMDPs combine the strength of hidden Markov Model (HMM) (capturing dynamics that depend on unobserved states) and that of Markov decision process (MDP) (taking the  ...  This makes the decentralized partially observable Markov decision process (DEC-POMDP) a more suitable tool to model the scheduling for the distributed system.  ... 
doi:10.1007/978-3-319-75683-7_15 fatcat:llbov47mcjd7jiplo3frruzmrq

Configurable numerical analysis for stochastic systems

Kristof Marussy, Attila Klenik, Vince Molnar, Andras Voros, Miklos Telek, Istvan Majzik
2016 2016 International Workshop on Symbolic and Numerical Methods for Reachability Analysis (SNR)  
Stochastic aspects of complex systems require more and more involved analysis approaches.  ...  Answering reachability and related analysis questions can often be reduced to steadystate, transient, reward or sensitivity value analysis of stochastic models.  ...  INTRODUCTION U NCERTAINTY of complex, asynchronous or hybrid systems can be captured by stochastic models.  ... 
doi:10.1109/snr.2016.7479383 fatcat:gi3k2l75lrhuxcapoeionmb35e
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