Learning to Select Promising Initial Solutions for Large Neighborhood Search-Based Multi-Agent Path Finding

Abstract

Full Citation:

Huber, Marc, Raidl, Günther R., Blum, Christian. Learning to Select Promising Initial Solutions for Large Neighborhood Search-Based Multi-Agent Path Finding. Computer Aided Systems Theory – EUROCAST 2024 (Quesada-Arencibia, Alexis and Affenzeller, Michael and Moreno-D'iaz, Roberto), volume 15172 of LNCS, pages 236-250, 2025, Springer.

Günther Raidl

Günther Raidl is a Professor at the Algorithms and Complexity Group.