Abstract: In this study, we propose and develop a Machine Learning-based metasolver for the Multi-Agent Path Finding (MAPF) problem, with the aim of selecting the most suitable solver based on the ...
Abstract: This article devises a two-phase Kriging-assisted evolutionary algorithm (named TEA) to tackle expensive constrained multiobjective optimization problems (CMOPs). In the first phase, only ...
The National Bureau of Economic Research has published a new working paper by economists Ali Shourideh (Carnegie Mellon ...
Every day, algorithms make consequential decisions about millions of people's lives—who gets approved for a mortgage, who is called back for a job interview, who receives priority care in a hospital ...
AI recommendations are decided upstream. Understand the 10-gate pipeline, where brands fail, and how small improvements ...
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