Quantitative Evaluation of Systems

Table of Contents

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   Book Overview
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   Chapter 1 End-User Probabilistic Programming
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   Chapter 2 The Logical Path to Autonomous Cyber-Physical Systems
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   Chapter 3 Model Checking Constrained Markov Reward Models with Uncertainties
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   Chapter 4 A Modest Approach to Modelling and Checking Markov Automata
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   Chapter 5 Finite Approximation of LMPs for Exact Verification of Reachability Properties
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   Chapter 6 Bayes-Adaptive Planning for Data-Efficient Verification of Uncertain Markov Decision Processes
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   Chapter 7 Strategy Representation by Decision Trees with Linear Classifiers
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   Chapter 8 Neural Network Precision Tuning
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    Chapter 9 SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes
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    Chapter 10 Fast Falsification of Hybrid Systems Using Probabilistically Adaptive Input
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    Chapter 11 State-Space Construction of Hybrid Petri Nets with Multiple Stochastic Firings
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    Chapter 12 Expected Cost Analysis of Attack-Defense Trees
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    Chapter 13 A Process Algebra for (Delimited) Persistent Stochastic Non-Interference
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    Chapter 14 Automated Game-Theoretic Verification of Security Systems
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    Chapter 15 Bayesian Abstraction of Markov Population Models
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    Chapter 16 UTOPIC: Under-Approximation Through Optimal Control
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    Chapter 17 Reducing Spreading Processes on Networks to Markov Population Models
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    Chapter 18 Doping Tests for Cyber-Physical Systems
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    Chapter 19 Safety Guarantees for the Electricity Grid with Significant Renewables Generation
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    Chapter 20 W ise M ove : A Framework to Investigate Safe Deep Reinforcement Learning for Autonomous Driving
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    Chapter 21 Great-Nsolve : A Tool Integration for (Markov Regenerative) Stochastic Petri Nets