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Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning [2022]

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