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Williamson (2001).pdf

FS01-04-021.pdf
Preview of Williamson (2001)
🔗 Source: aaai.org
📊 Size: 763 KB
👤 Author: Jon Williamson
⬇️ Downloads: 138

Summary

Bayesian networks can be applied to logical reasoning under uncertainty, similar to their use in causal reasoning. Despite deductive logic dealing with certain truths, logical reasoning often occurs in uncertain contexts, such as searching for proofs or evaluating mathematical conjectures. Bayesian networks, consisting of a directed acyclic graph and probability specifications, can efficiently represent probability distributions over logical clauses and be used for tasks like proof planning. The approach is based on identifying analogies between causal and logical influence, with logical implication being an influence relation that allows the application of Bayesian networks to logical reasoning.

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Bayesian networks can be applied to logical reasoning under uncertainty, similar to their use in causal reasoning.

Technical Information

  • File Format: PDF
  • File Size: 763 KB
  • Pages: 8
  • Language: EN
  • Author: Jon Williamson
  • Total Downloads: 138
  • Last Updated: 3 weeks ago

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