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A History of Probabilistic Inductive Logic Programming
Frontiers in Robotics and AI, 2014 The field of Probabilistic Logic Programming (PLP) has seen significant advances in the last 20 years, with many proposals for languages that combine probability with logic programming.
Fabrizio eRiguzzi +2 more
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Numerical Markov Logic Network: A Scalable Probabilistic Framework for Hybrid Knowledge Inference
Information, 2021 In recent years, the Markov Logic Network (MLN) has emerged as a powerful tool for knowledge-based inference due to its ability to combine first-order logic inference and probabilistic reasoning.
Ping Zhong +4 more
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Probabilistic Logics and Probabilistic Networks
, 2011 While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches to probabilistic logic into a simple unifying ...
Romeijn, J.W. +3 more
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Probabilistic description logic programs [PDF]
International Journal of Approximate Reasoning, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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ProbLog2: Probabilistic Logic Programming [PDF]
, 2015 We present ProbLog2, the state of the art implementation of the probabilistic programming language ProbLog. The ProbLog language allows the user to intuitively build programs that do not only encode complex interactions between a large sets of heterogenous components but also the inherent uncertainties that are present in real-life situations.
Dries, Anton +6 more
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Learning probabilistic logic models from probabilistic examples [PDF]
Machine Learning, 2008 We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset ...
Chen, J, Muggleton, S, Santos, J
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Entropy, 2015 For conditional probabilistic knowledge bases with conditionals based on propositional logic, the principle of maximum entropy (ME) is well-established, determining a unique model inductively completing the explicitly given knowledge.
Christoph Beierle +2 more
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Probability-Based Centralized Device for Spectrum Handoff in Cognitive Radio Networks
IEEE Access, 2019 Wireless communication technology is the future of communication, but rapid growth in wireless technology has led to a scarcity in the spectrum. Thus, the world has moved away from fixed spectrum allocation to dynamic spectrum allocation. Cognitive radio
Manav Aggarwal +5 more
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Probability Logic for Harsanyi Type Spaces [PDF]
Logical Methods in Computer Science, 2014 Probability logic has contributed to significant developments in belief types for game-theoretical economics. We present a new probability logic for Harsanyi Type spaces, show its completeness, and prove both a de-nesting property and a unique extension ...
Chunlai Zhou
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On-Line Surface Roughness Prediction by Using a Probabilistic Approach for End-Milling
IEEE Access, 2019 An effective and efficient methodology is proposed to predict surface roughness by online monitoring of surface quality using accelerometer signals. A probabilistic approach, Monte Carlo Simulation, was researched and developed to create an automated ...
Oguz Kayabasi, Senol Erturk
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