Reasoning with real-valued first order logic and probability intervals
AssigneeInternational Business Machines Corporation
InventorRadu MARINESCU
Life of this patent
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Abstract
Embodiments are provided for providing enhanced routing in a computing system by a processor. All first-order logic formulas may be converted into real-valued logic formulas. A probabilistic inference is executed using the real-valued logic formulas and one or more probability intervals associated with an atomic formulae in a knowledge base to provide an interval conditional probability indicating that a first predicate condition is true based one or more alternative predicates being true.
Claims20
A method for providing enhanced automated reasoning in a computing environment by one or more processors comprising:
- executing machine learning logic to convert all first-order logic formulas into real-valued logic formulas, wherein the real-valued logic formulas are input as training data into a logical neural network (“LNN”);
- and
- generating the LNN by using the training data to execute a probabilistic inference using the real-valued logic formulas and one or more probability intervals associated with an atomic formulae in a knowledge base to provide an interval conditional probability indicating that a first predicate condition is true based one or more alternative predicates being true.
A system for providing enhanced automated reasoning in a computing environment, comprising:
- one or more computers with executable instructions that when executed cause the system to:
- execute machine learning logic to convert all first-order logic formulas into real-valued logic formulas, wherein the real-valued logic formulas are input as training data into a logical neural network (“LNN”);
- and
- generate the LNN by using the training data to execute a probabilistic inference using the real-valued logic formulas and one or more probability intervals associated with an atomic formulae in a knowledge base to provide an interval conditional probability indicating that a first predicate condition is true based one or more alternative predicates being true.
A computer program product for providing enhanced automated reasoning in a computing environment, the computer program product comprising:
- one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instruction comprising:
- program instructions to execute machine learning logic to convert all first-order logic formulas into real-valued logic formulas, wherein the real-valued logic formulas are input as training data into a logical neural network (“LNN”);
- and
- program instructions to generate the LNN by using the training data to execute a probabilistic inference using the real-valued logic formulas and one or more probability intervals associated with an atomic formulae in a knowledge base to provide an interval conditional probability indicating that a first predicate condition is true based one or more alternative predicates being true.
Dependencies are inferred from the claim text.