Veröffentlichung

Titel:

Integrating Typed Model Counting into First-Order Maximum Entropy Computations and the Connection to Markov Logic Networks

AutorInnen:

Marco Wilhelm
Gabriele Kern-Isberner
Marc Finthammer
Christoph Beierle

Kategorie:

Konferenzbandbeiträge

erschienen in:

Proceedings of the 32nd International Florida Artificial Intelligence Research Society Conference (FLAIRS-2019), pp. 494-499 (2019)

Abstract:

The principle of maximum entropy (MaxEnt) provides a well-founded methodology for commonsense reasoning based on probabilistic conditional knowledge. We show how to calculate MaxEnt distributions in a first-order setting by using typed model counting and condensed iterative scaling. Further, we discuss the connection to Markov Logic Networks for drawing inferences.

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BibTeX-Eintrag:

@InProceedings{WilhelmKern-IsbernerFinthammerBeierle2019a, author = {Marco Wilhelm and Gabriele Kern{-}Isberner and Marc Finthammer and Christoph Beierle}, title = {Integrating Typed Model Counting into First-Order Maximum Entropy Computations and the Connection to Markov Logic Networks}, booktitle = {Proceedings of the 32nd International Florida Artificial Intelligence Research Society Conference ({FLAIRS}-2019)}, year = {2019}, editor = {Roman Bart{\'{a}}k and Keith W. Brawner}, pages = {494--499}, publisher = {{AAAI} Press}, url = {https://aaai.org/ocs/index.php/FLAIRS/FLAIRS19/paper/view/18235}, }