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Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning

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Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning
Springer Nature Switzerland

Table of Contents

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    Book Overview
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    Chapter 1 Rigorous Engineering of Collective Adaptive Systems Introduction to the 4 th Track Edition
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    Chapter 2 Correct by Design Coordination of Autonomous Driving Systems
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    Chapter 3 Neural Predictive Monitoring for Collective Adaptive Systems
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    Chapter 4 An Extension of HybridSynchAADL and Its Application to Collaborating Autonomous UAVs
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    Chapter 5 Discrete Models of Continuous Behavior of Collective Adaptive Systems
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    Chapter 6 Modelling Flocks of Birds from the Bottom Up
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    Chapter 7 Towards Drone Flocking Using Relative Distance Measurements
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    Chapter 8 Epistemic Ensembles
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    Chapter 9 A Modal Approach to Consciousness of Agents
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    Chapter 10 An Experimental Toolchain for Strategy Synthesis with Spatial Properties
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    Chapter 11 Toward a Kinetic Framework to Model the Collective Dynamics of Multi-agent Systems
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    Chapter 12 Understanding Social Feedback in Biological Collectives with Smoothed Model Checking
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    Chapter 13 Efficient Estimation of Agent Networks
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    Chapter 14 Attuning Adaptation Rules via a Rule-Specific Neural Network
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    Chapter 15 Measuring Convergence Inertia: Online Learning in Self-adaptive Systems with Context Shifts
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    Chapter 16 Capturing Dependencies Within Machine Learning via a Formal Process Model
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    Chapter 17 On Model-Based Performance Analysis of Collective Adaptive Systems
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    Chapter 18 Programming Multi-robot Systems with X-KLAIM
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    Chapter 19 Bringing Aggregate Programming Towards the Cloud
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    Chapter 20 Ensemble-Based Modeling Abstractions for Modern Self-optimizing Systems
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    Chapter 21 Formal Analysis of Lending Pools in Decentralized Finance
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    Chapter 22 A Rewriting Framework for Interacting Cyber-Physical Agents
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    Chapter 23 Model Checking Reconfigurable Interacting Systems
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    Chapter 24 Formal Methods Meet Machine Learning (F3ML)
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    Chapter 25 The Modest State of Learning, Sampling, and Verifying Strategies
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    Chapter 26 Importance Splitting in Uppaal
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    Chapter 27 Verification of Variability-Intensive Stochastic Systems with Statistical Model Checking
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Title
Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning
Published by
Springer Nature Switzerland, October 2022
DOI 10.1007/978-3-031-19759-8
ISBNs
978-3-03-119758-1, 978-3-03-119759-8
Editors

Margaria, Tiziana, Steffen, Bernhard

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