Lower complexity bounds for lifted inference

DOI10.1017/S1471068413000707zbMath1379.68298arXiv1204.3255MaRDI QIDQ4592980

Manfred Jaeger

Publication date: 9 November 2017

Published in: Theory and Practice of Logic Programming (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1204.3255

zbMATH Keywords

lifted inferenceprobabilistic-logic models

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic in artificial intelligence (68T27) Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.) (68Q17)

Related Items (3)

The complexity of Bayesian networks specified by propositional and relational languages ⋮ The finite model theory of Bayesian network specifications: descriptive complexity and zero/one laws ⋮ Weighted First-Order Model Counting in the Two-Variable Fragment With Counting Quantifiers

Uses Software

• BLOG

Cites Work

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• Probabilistic Horn abduction and Bayesian networks
• On the complexity of inference about probabilistic relational models
• Markov logic networks
• Representing Causal Information About a Probabilistic Process
• Probabilities on finite models

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