Searching for the M Best Solutions in Graphical Models
نویسندگان
چکیده
منابع مشابه
SEARCHING FOR M BEST SOLUTIONS IN GRAPHICAL MODELS Searching For M Best Solutions In Graphical Models
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 bestfirst al...
متن کاملSEARCHING FOR THE M BEST SOLUTIONS IN GRAPHICAL MODELS Searching For The M Best Solutions In Graphical Models
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 mA*, extending the well-known A* to them-best task, and for the first time prove that all its desirable properties, including soundness, completeness and optimal efficiency, are maintained. Since bestfirst algo...
متن کاملSearching for the M Best Solutions in Graphical Models
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 mA*, extending the well-known A* to them-best task, and for the first time prove that all its desirable properties, including soundness, completeness and optimal efficiency, are maintained. Since bestfirst algo...
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Bucket elimination is an algorithmic framework that generalizes dynamic programming to accommodate many problem-solving and reasoning tasks. In particular, it can be used for any combinatorial optimization task such as finding most probable configurations in a Bayesian network. In this paper we present a new algorithm elim-m-opt, extending bucket elimination for the task of finding m best solut...
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The paper focuses on finding the m best solutions to combinatorial optimization problems using Best-First or Branchand-Bound search. Specifically, we present m-A*, extending the well-known A* to the m-best task, and prove that all its desirable properties, including soundness, completeness and optimal efficiency, are maintained. Since Best-First algorithms have memory problems, we also extend t...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2016
ISSN: 1076-9757
DOI: 10.1613/jair.4985