Probabilistic knowledge representation using the principle of maximum entropy and Gröbner basis theory
DOI10.1007/s10472-015-9457-7zbMath1420.68203OpenAlexW588585258MaRDI QIDQ513343
Christoph Beierle, Marco Wilhelm, Gabriele Kern-Isberner
Publication date: 6 March 2017
Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10472-015-9457-7
Logic in artificial intelligence (68T27) Knowledge representation (68T30) Reasoning under uncertainty in the context of artificial intelligence (68T37) Gröbner bases; other bases for ideals and modules (e.g., Janet and border bases) (13P10) Measures of information, entropy (94A17)
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