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Quantitative evaluation of systems : 16th International Conference, QEST 2019, Glasgow, UK, September 10-12, 2019, proceedings

Author: David Parker; Verena Wolf
Publisher: Cham, Switzerland : Springer, [2019]
Series: Lecture notes in computer science, 11785.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Summary:
This book constitutes the proceedings of the 16th International Conference on Quantitative Evaluation Systems, QEST 2019, held in Glasgow, UK, in September 2019. The 17 full papers presented together with 2 short papers were carefully reviewed and selected from 40 submissions. The papers cover topics in the field of Probabilistic Verification; Learning and Verification; Hybrid Systems; Security; Probabilistic  Read more...
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Genre/Form: Electronic books
Conference papers and proceedings
Congresses
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: David Parker; Verena Wolf
ISBN: 9783030302818 3030302814
OCLC Number: 1120082809
Description: 1 online resource (xi, 361 pages) : illustrations (some color).
Contents: Intro; Preface; Organization; Contents; Invited Talks; End-User Probabilistic Programming; 1 Introduction; 1.1 Background: Spreadsheets and End-User Programming; 1.2 Background: Probabilistic Programming; 1.3 Bringing Probabilistic Programming to the Spreadsheet; 1.4 How Would Probabilistic Programming Help Spreadsheet Users?; 2 Spreadsheet Extensions for Uncertainty; 2.1 Example: Clara's Budget; 2.2 Managing Uncertainty with Uncertain Values; 2.3 Managing Uncertainty with Sheet-Defined Functions; 3 End-User Behaviour with Uncertainty; 3.1 Interview Study; 3.2 Findings 4 Design Implications of the Interview Study5 Conclusions; References; The Logical Path to Autonomous Cyber-Physical Systems; 1 Introduction; 2 Challenge; 3 Approach; 4 Summary and Outlook; References; Probabilistic Verification; Model Checking Constrained Markov Reward Models with Uncertainties; 1 Introduction; 2 Preliminaries and Notation; 3 Markov Reward Models; 4 Constrained Markov Reward Models; 5 Analysing Bisimilarity on Constrained MRMs; 6 Model Checking Constrained MRMs; 7 Markov Models with Stochastic Rewards; 8 Conclusion; References A Modest Approach to Modelling and Checking Markov Automata1 Introduction; 2 Markov Automata; 3 Modelling; 3.1 Modest for Markov Automata; 3.2 Alternative Modelling Languages; 4 Algorithms; 4.1 Untimed and Expected-Reward Properties; 4.2 Time-Bounded Reachability; 4.3 Long-Run Average Rewards; 4.4 Other Verification Problems; 5 Experiments; 5.1 mcsta and Imca; 5.2 mcsta and Storm; 6 Conclusion; References; Finite Approximation of LMPs for Exact Verification of Reachability Properties; 1 Introduction; 2 Preliminaries; 3 The Mean MDP; 3.1 Mean of a Probability Transition; 3.2 From LMP to MDP 3.3 The Reachability Property in S and S_U4 Analysis of the Mean MDP; 4.1 Possible Extension, Simplification and Reusability; 4.2 Error Analysis at Implementation --
Comparison of S_ and S_""0362S_; 5 Conclusion; References; Learning and Verification; Bayes-Adaptive Planning for Data-Efficient Verification of Uncertain Markov Decision Processes; 1 Introduction; 1.1 Related Work; 2 Rudiments; 2.1 Markov Decision Processes; 2.2 Strategies; 2.3 Bayesian Reinforcement Learning (Bayesian RL); 2.4 PCTL Properties; 3 Verification and Learning; 3.1 Parameter Synthesis; 3.2 Bayesian Inference 3.3 Confidence Computation3.4 Overview of the Approach; 4 Active Learning; 4.1 Bayes-Adaptive Model; 4.2 Synthesis of Bayes-Adaptive Strategies; 4.3 Bayes-Adaptive Temporal Difference Search; 5 Experiments; 5.1 Setup; 5.2 Results; 6 Conclusions and Future Work; References; Strategy Representation by Decision Trees with Linear Classifiers; 1 Introduction; 2 Stochastic Graph Games and Strategies; 3 Decision Trees and Decision Tree Learning; 4 Decision Trees with Linear Classifiers; 4.1 Linear Classifiers in the Leaf Nodes; 4.2 Splitting Criterion for Small Decision Trees with Classifiers
Series Title: Lecture notes in computer science, 11785.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Responsibility: David Parker, Verena Wolf (eds.).

Abstract:

This book constitutes the proceedings of the 16th International Conference on Quantitative Evaluation Systems, QEST 2019, held in Glasgow, UK, in September 2019.The 17 full papers presented together  Read more...

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