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Searching for the M Best Solutions in Graphical Models
2016
The Journal of Artificial Intelligence Research
The paper focuses on finding the m best solutions to combinatorial optimization problems using best-first or depth-first branch and bound search. Specifically, we present a new algorithm m-A*, extending the well-known A* to the m-best task, and for the first time prove that all its desirable properties, including soundness, completeness and optimal efficiency, are maintained. Since best-first algorithms require extensive memory, we also extend the memory-efficient depth-first branch and bound
doi:10.1613/jair.4985
fatcat:dfrabapwsvcxlme4yo65f7zuuq