Results 11 to 20 of about 224,550 (312)
Probabilistic Inductive Logic Programming [PDF]
, 2008 Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning.
Luc De Raedt, Kristian Kersting
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Neural Probabilistic Logic Programming in Discrete-Continuous Domains [PDF]
Conference on Uncertainty in Artificial Intelligence, 2023 Neural-symbolic AI (NeSy) allows neural networks to exploit symbolic background knowledge in the form of logic. It has been shown to aid learning in the limited data regime and to facilitate inference on out-of-distribution data.
Lennert De Smet +5 more
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Nonground Abductive Logic Programming with Probabilistic Integrity Constraints [PDF]
Theory and Practice of Logic Programming, 2021 Uncertain information is being taken into account in an increasing number of application fields. In the meantime, abduction has been proved a powerful tool for handling hypothetical reasoning and incomplete knowledge.
Elena Bellodi +4 more
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Probabilistic Logic Programming Semantics For Procedural Content Generation
Artificial Intelligence and Interactive Digital Entertainment Conference, 2023 Research in procedural content generation (PCG) has recently heralded two major methodologies: machine learning (PCGML) and declarative programming. The former shows promise by automating the specification of quality criteria through latent patterns in ...
Abdelrahman Madkour +4 more
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Studying Transaction Fees in the Bitcoin Blockchain with Probabilistic Logic Programming
Information, 2019 In Bitcoin, if a miner is able to solve a computationally hard problem called proof of work, it will receive an amount of bitcoin as a reward which is the sum of the fees for the transactions included in a block plus an amount inversely proportional to ...
Damiano Azzolini +2 more
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Explanations as Programs in Probabilistic Logic Programming [PDF]
Fuji International Symposium on Functional and Logic Programming, 2022 The generation of comprehensible explanations is an essential feature of modern artificial intelligence systems. In this work, we consider probabilistic logic programming, an extension of logic programming which can be useful to model domains with ...
Germán Vidal
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Probabilistic (logic) programming concepts [PDF]
Machine Learning, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
De Raedt, Luc, Kimmig, Angelika
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Probabilistic call by push value [PDF]
Logical Methods in Computer Science, 2019 We introduce a probabilistic extension of Levy's Call-By-Push-Value. This extension consists simply in adding a " flipping coin " boolean closed atomic expression. This language can be understood as a major generalization of Scott's PCF encompassing both
Thomas Ehrhard, Christine Tasson
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A probabilistic logic programming event calculus [PDF]
Theory and Practice of Logic Programming, 2014 AbstractWe present a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities (STA) detected on video frames. The output is a set of recognised long-term activities (LTA), which are pre-defined temporal combinations of STA.
Skarlatidis, Anastasios +3 more
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Probabilistic Logic Programming with Beta-Distributed Random Variables [PDF]
AAAI Conference on Artificial Intelligence, 2018 We enable aProbLog—a probabilistic logical programming approach—to reason in presence of uncertain probabilities represented as Beta-distributed random variables.
F. Cerutti +3 more
semanticscholar +4 more sources