Probabilistic Logic Programming under Maximum Entropy
<p>In this paper, we focus on the combination of probabilistic logic programming with the principle of maximum entropy. We start by defining probabilistic queries to probabilistic logic programs and their answer substitutions under maximum entropy. We then present an efficient linear programmi...
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| Μορφή: | Conference item |
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Springer
1999
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| _version_ | 1826284383417401344 |
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| author | Lukasiewicz, T Kern−Isberner, G |
| author_facet | Lukasiewicz, T Kern−Isberner, G |
| author_sort | Lukasiewicz, T |
| collection | OXFORD |
| description | <p>In this paper, we focus on the combination of probabilistic logic programming with the principle of maximum entropy. We start by defining probabilistic queries to probabilistic logic programs and their answer substitutions under maximum entropy. We then present an efficient linear programming characterization for the problem of deciding whether a probabilistic logic program is satisfiable. Finally, and as a central contribution of this paper, we introduce an efficient technique for approximative probabilistic logic programming under maximum entropy. This technique reduces the original entropy maximization task to solving a modified and relatively small optimization problem.</p> |
| first_indexed | 2024-03-07T01:13:01Z |
| format | Conference item |
| id | oxford-uuid:8db043e1-b3f1-4a3f-8f99-1bcf1acb77a1 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T01:13:01Z |
| publishDate | 1999 |
| publisher | Springer |
| record_format | dspace |
| spelling | oxford-uuid:8db043e1-b3f1-4a3f-8f99-1bcf1acb77a12022-03-26T22:52:45ZProbabilistic Logic Programming under Maximum EntropyConference itemhttp://purl.org/coar/resource_type/c_5794uuid:8db043e1-b3f1-4a3f-8f99-1bcf1acb77a1Department of Computer ScienceSpringer1999Lukasiewicz, TKern−Isberner, G<p>In this paper, we focus on the combination of probabilistic logic programming with the principle of maximum entropy. We start by defining probabilistic queries to probabilistic logic programs and their answer substitutions under maximum entropy. We then present an efficient linear programming characterization for the problem of deciding whether a probabilistic logic program is satisfiable. Finally, and as a central contribution of this paper, we introduce an efficient technique for approximative probabilistic logic programming under maximum entropy. This technique reduces the original entropy maximization task to solving a modified and relatively small optimization problem.</p> |
| spellingShingle | Lukasiewicz, T Kern−Isberner, G Probabilistic Logic Programming under Maximum Entropy |
| title | Probabilistic Logic Programming under Maximum Entropy |
| title_full | Probabilistic Logic Programming under Maximum Entropy |
| title_fullStr | Probabilistic Logic Programming under Maximum Entropy |
| title_full_unstemmed | Probabilistic Logic Programming under Maximum Entropy |
| title_short | Probabilistic Logic Programming under Maximum Entropy |
| title_sort | probabilistic logic programming under maximum entropy |
| work_keys_str_mv | AT lukasiewiczt probabilisticlogicprogrammingundermaximumentropy AT kernisbernerg probabilisticlogicprogrammingundermaximumentropy |