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Markov Logic Networks Asymptotics Explored in New Research

By PulseAugur Editorial · [1 sources] ·

Researchers have analyzed the asymptotic behavior of Markov logic networks (MLNs) as their domain size approaches infinity. The study demonstrates that under mild assumptions, MLNs with positive-weight soft constraints will diverge from uniform distributions for sufficiently large domains. For languages with relation symbols of arity 1, the research provides a characterization of MLN asymptotic behaviors, showing that MLNs and lifted Bayesian networks can define different distributions on structures. AI

RANK_REASON This is a research paper published on arXiv detailing theoretical analysis of Markov logic networks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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Markov Logic Networks Asymptotics Explored in New Research

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This is a research paper published on arXiv detailing theoretical analysis of Markov logic networks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Vera Koponen ·

    Domain size asymptotics for Markov logic networks

    arXiv:2509.04192v2 Announce Type: replace Abstract: A Markov logic network (MLN) $\mathbb{M}$ determines a probability distribution $\mathbb{P}_n^\mathbb{M}$ on the set $\mathbf{W}_n$ of structures, or ``possible worlds'', with domain $\{1, \ldots, n\}$. We study the properties o…

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