J. Mańdziuk

Analyzing search behavior of population-based optimization algorithms using graph neural networks

This paper proposes to represent complete execution trajectories as graphs and learn their embeddings using graph neural networks and shows that the learned embeddings can effectively distinguish between algorithms even when evaluated across diverse benchmark functions.