AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A novel framework for analyzing metastability using Koopman theory is proposed, using a finite set of system trajectories to learn a representation of the dynamics that defines a latent space in which the system evolves linearly, thereby enabling a systematic characterization of metastable behavior through the spectral...
This work proposes a new quantitative semantics for STL having several desirable properties, making it suitable for reward generation, and establishes the new semantics to be the most suitable for synthesizing feedback controllers for complex continuous dynamical systems through reinforcement learning.
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