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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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Probabilistic Neighbourhood Logic
2000This paper presents a probabilistic extension of Neighbourhood Logic (NL[14,1],). The study of such an extension is motivated by the need to supply the Probabilistic Duration Calculus (PDC,[10,4]) with a proof system. The relation between the new logic and PDC is similar to that between DC [15] and ITL [12,3]. We present a complete proof system for the
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2001
The notion of “vagueness” must be sharply distinguished from the notion of “uncertainty”. Accordingly, fuzzy logic must be sharply distinguished from probabilistic logic. Indeed, a graded truth value for a formula α mustn’t be confused with a measure of our degree of belief in α.
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The notion of “vagueness” must be sharply distinguished from the notion of “uncertainty”. Accordingly, fuzzy logic must be sharply distinguished from probabilistic logic. Indeed, a graded truth value for a formula α mustn’t be confused with a measure of our degree of belief in α.
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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
Logic gates based on neuristors made from two-dimensional materials
Nature Electronics, 2021Chunsen liu, Jianlu Wang, Weida Hu
exaly