Research Output
Maximum Entropy in Nilsson's Probabilistic Logic
  Nilsson's Probabilistic Logic is a set theoretic mechanism for reasoning with uncertainty. We propose a new way of looking at the probability constraints enforced by the framework, which allows the expert to include conditional probabilities in the semantic tree, thus making Probabilistic Logic more expressive. An algorithm is presented which will find the maximum entropy point probability for a rule of entailment without resorting to solution by iterative approximation. The algorithm works for both the propositional and the predicate logic. Also presented are a number of methods for employing the conditional probabilities.

  • Date:

    15 August 2017

  • Publication Status:

    Published

  • Publisher

    International Joint Conferences on Artificial Intelligence Organization

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    004 Data processing & computer science

  • Funders:

    Heriot Watt University

Citation

Kane, T. B. (2017). Maximum Entropy in Nilsson's Probabilistic Logic. In Proceedings of the 11th International Joint Conference on Artificial Intelligence (452-457)

Authors

Keywords

Reasoning, probability,

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