Transferable knowledge graphs with executable learned operators for algorithm design
This work introduces Generative Executable Algorithm Knowledge Graphs (GEAKG), a representation in which this knowledge is stored as a generative, executable, transferable graph: typed nodes hold validated operators, edges encode admissible compositions, and learned edge weights record effective sequences.
Camilo Chacón Sartori, Jos'e H. Garc'ia, Andrei Tomut et al.
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