Results 21 to 30 of about 189,472 (279)
Weighted versus Probabilistic Logics [PDF]
, 2009 While a mature theory around logics such as MSO, LTL, and CTL has been developed in the pure boolean setting of finite automata, weighted automata lack such a natural connection with (temporal) logic and related verification algorithms. In this paper, we will identify weighted versions of MSO and CTL that generalize the classical logics and even other ...
Gastin, Paul, Bollig, Benedikt
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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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Revisiting bisimilarity and its modal logic for nondeterministic and probabilistic processes [PDF]
, 2013 We consider PML, the probabilistic version of Hennessy-Milner logic introduced by Larsen and Skou to characterize bisimilarity over probabilistic processes without internal nondeterminism.We provide two different interpretations for PML by considering ...
Bernardo, Marco +2 more
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Relational reasoning via probabilistic coupling [PDF]
, 2015 Probabilistic coupling is a powerful tool for analyzing pairs of probabilistic processes. Roughly, coupling two processes requires finding an appropriate witness process that models both processes in the same probability space.
A Zaks +7 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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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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Logical Characterizations of Behavioral Relations on Transition Systems of Probability Distributions [PDF]
, 2014 Probabilistic nondeterministic processes are commonly modeled as probabilistic LTSs (PLTSs). A number of logical characterizations of the main behavioral relations on PLTSs have been studied.
Crafa, Silvia, Ranzato, Francesco
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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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