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Probabilistic Planning in Hybrid Probabilistic Logic Programs
2007In this paper, we present a new approach to probabilistic planning based on logic programming, by relating probabilistic planning to hybrid probabilistic logic programs with probabilistic answer set semantics [32]. We show that any probabilistic planning problem, $\cal P$, can be translated into a hybrid probabilistic logic program whose probabilistic ...
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Deep probabilistic logic programming
2017Probabilistic logic programming under the distribution semantics has been very useful in machine learning. However, inference is expensive so machine learning algorithms may turn out to be slow. In this paper we consider a restriction of the language called hierarchical PLP in which clauses and predicates are hierarchically organized.
NGUEMBANG FADJA, Arnaud +2 more
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Modeling Smart Contracts with Probabilistic Logic Programming
Business Information Systems, 2020Damiano Azzolini +2 more
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Probabilistic Databases and Logic Programming
2001Uncertainty occurs in the world in many ways. For instance, image processing programs identify the content of images with some levels of uncertainty. Prediction programs predict when events will occur with certain probabilities. In this tutorial, I will focus on probabilistic methods to handle uncertainty.
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A Comparison of MCMC Sampling for Probabilistic Logic Programming
International Conference of the Italian Association for Artificial Intelligence, 2019Damiano Azzolini +3 more
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Logic-in-memory based on an atomically thin semiconductor
Nature, 2020Guilherme Migliato Marega +2 more
exaly
Gallium nitride-based complementary logic integrated circuits
Nature Electronics, 2021Zheyang Zheng, Li Zhang, Han Xu
exaly
Personalized Recommendations using Knowledge Graphs: A Probabilistic Logic Programming Approach
ACM Conference on Recommender Systems, 2016R. Catherine, William W. Cohen
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