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Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning [2022]
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Rigorous Engineering of Collective Adaptive Systems Introduction to the 4<sup>th</sup> Track Edition
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Correct by Design Coordination of Autonomous Driving Systems
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Neural Predictive Monitoring for Collective Adaptive Systems
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An Extension of HybridSynchAADL and Its Application to Collaborating Autonomous UAVs
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Discrete Models of Continuous Behavior of Collective Adaptive Systems
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Modelling Flocks of Birds from the Bottom Up
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Towards Drone Flocking Using Relative Distance Measurements
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Epistemic Ensembles
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A Modal Approach to Consciousness of Agents
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An Experimental Toolchain for Strategy Synthesis with Spatial Properties
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Toward a Kinetic Framework to Model the Collective Dynamics of Multi-agent Systems
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Understanding Social Feedback in Biological Collectives with Smoothed Model Checking
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Efficient Estimation of Agent Networks
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Attuning Adaptation Rules via a Rule-Specific Neural Network
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Measuring Convergence Inertia: Online Learning in Self-adaptive Systems with Context Shifts
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Capturing Dependencies Within Machine Learning via a Formal Process Model
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On Model-Based Performance Analysis of Collective Adaptive Systems
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Programming Multi-robot Systems with X-KLAIM
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Bringing Aggregate Programming Towards the Cloud
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Ensemble-Based Modeling Abstractions for Modern Self-optimizing Systems
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Formal Analysis of Lending Pools in Decentralized Finance
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A Rewriting Framework for Interacting Cyber-Physical Agents
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Model Checking Reconfigurable Interacting Systems
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Formal Methods Meet Machine Learning (F3ML)
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The Modest State of Learning, Sampling, and Verifying Strategies
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Importance Splitting in Uppaal
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Verification of Variability-Intensive Stochastic Systems with Statistical Model Checking