AI RESEARCH
GeoPAS: Geometric Probing for Algorithm Selection in Continuous Black-Box Optimisation
arXiv CS.LG
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ArXi:2604.09095v1 Announce Type: new Automated algorithm selection in continuous black-box optimisation typically relies on fixed landscape descriptors computed under a limited probing budget, yet such descriptors can degrade under problem-split or cross-benchmark evaluation. We propose GeoPAS, a geometric probing approach that represents a problem instance by multiple coarse two-dimensional slices sampled across locations, orientations, and logarithmic scales.