Results 241 to 250 of about 189,472 (279)
Some of the next articles are maybe not open access.
2011
We define an extension of stit logic that encompasses subjective probabilities representing beliefs about simultaneous choice exertion of other agents. This semantics enables us to express that an agent sees to it that a condition obtains under a minimal chance of success.
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We define an extension of stit logic that encompasses subjective probabilities representing beliefs about simultaneous choice exertion of other agents. This semantics enables us to express that an agent sees to it that a condition obtains under a minimal chance of success.
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Probabilistic Dynamic Epistemic Logic
Journal of Logic, Language and Information, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Probabilistic Logic and Induction
Journal of Logic and Computation, 2005Summary: We give a probabilistic interpretation of first-order formulas based on Valiant's model of pac-learning. We study the resulting notion of probabilistic or approximate truth and take some first steps in developing its model theory. In particular we show that every fixed error parameter determining the precision of universal quantification gives
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2013
In a seminal paper Goldfarb (1979) points out that ”The connection between quantifiers and choice functions or, more precisely, between quantifier-dependence and choice functions, is at the heart of how classical logicians in the twenties viewed the nature of quantification.” (Goldfarb 1979, p. 357).
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In a seminal paper Goldfarb (1979) points out that ”The connection between quantifiers and choice functions or, more precisely, between quantifier-dependence and choice functions, is at the heart of how classical logicians in the twenties viewed the nature of quantification.” (Goldfarb 1979, p. 357).
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Probabilistic Entailment and a Non-Probabilistic Logic
Logic Journal of IGPL, 2003Let \(L\) be a finite language of propositional logic. We say that \(\Gamma\), a set of \(m\) sentences of \(L\), \(\{\theta_1, \ldots \theta_m\}\) with probabilities \(\{\eta_1, \ldots, \eta_m\}\), \((\vec{e},\zeta)\)-entails \(\psi\) provided that the probability of \(\psi\) is at least \(\zeta\) for all probability functions \(P\) for which \(P ...
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2020
This chapter presents the proof-theoretical and model-theoretical approaches to reasoning about time and probability. Three different ways of combining probabilistic and temporal modalities are presented, and well defined syntax and corresponding semantics is provided for every formalism.
Doder, Dragan, Perovic, Aleksandar
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This chapter presents the proof-theoretical and model-theoretical approaches to reasoning about time and probability. Three different ways of combining probabilistic and temporal modalities are presented, and well defined syntax and corresponding semantics is provided for every formalism.
Doder, Dragan, Perovic, Aleksandar
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1990
Because many artificial intelligence applications require the ability to reason with uncertain knowledge, it is important to seek appropriate generalizations of logic for that case. Nils J. Nilsson [1] presented a semantical generalization of logic in which the truth values of sentences are probability values between 0 and 1.
Jiwen Guan, Victor R. Lesser
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Because many artificial intelligence applications require the ability to reason with uncertain knowledge, it is important to seek appropriate generalizations of logic for that case. Nils J. Nilsson [1] presented a semantical generalization of logic in which the truth values of sentences are probability values between 0 and 1.
Jiwen Guan, Victor R. Lesser
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Probabilistic Automata and Probabilistic Logic
2012We present a monadic second-order logic which is extended by an expected value operator and show that this logic is expressively equivalent to probabilistic automata for both finite and infinite words. We give possible syntax extensions and an embedding of our probabilistic logic into weighted MSO logic. We further derive decidability results which are
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Optochemical Control of DNA‐Switching Circuits for Logic and Probabilistic Computation
Angewandte Chemie - International Edition, 2021Mingshu Xiao, Wei Lai, Li Li
exaly
Neural probabilistic logic programming in DeepProbLog
Artificial Intelligence, 2021Robin Manhaeve +2 more
exaly

