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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 12045319 B1

PDFFull Text
Date of Patent:
Jul. 23, 2024

Filed:

Oct. 06, 2020

First-order logical neural networks with bidirectional inference

Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Ryan Nelson Riegel, Carrollton, GA (US);

Francois Pierre Luus, Wierdapark, ZA;

Ismail Yunus Akhalwaya, Emmarentia, ZA;

Naweed Aghmad Khan, Johannesburg, ZA;

Ndivhuwo Makondo, Pretoria, ZA;

Francisco Barahona, White Plains, NY (US);

Alexander Gray, Yonkers, NY (US);

Assignee:

International Business Machines Corporation, Armonk, NY (US);

Attorneys:

Scully, Scott, Murphy & Presser, P.C.

Shimon Benjamin

Primary Examiner:

Alan Chen

Int. Cl.
CPC ...
G06F 18/20 (2023.01); G06F 18/214 (2023.01); G06N 3/04 (2023.01); G06N 3/063 (2023.01); G06N 3/08 (2023.01); G06N 5/025 (2023.01); G06N 5/04 (2023.01); G06N 5/046 (2023.01);
U.S. Cl.
CPC ...
G06F 18/29 (2023.01); G06F 18/214 (2023.01); G06N 3/04 (2013.01); G06N 3/063 (2013.01); G06N 3/08 (2013.01); G06N 5/025 (2013.01); G06N 5/042 (2013.01); G06N 5/046 (2013.01);
Abstract

A system for configuring and using a logical neural network including a graph syntax tree of formulae in a represented knowledgebase connected to each other via nodes representing each proposition. One neuron exists for each logical connective occurring in each formula and, additionally, one neuron for each unique proposition occurring in any formula. All neurons return pairs of values representing upper and lower bounds on truth values of their corresponding subformulae and propositions. Neurons corresponding to logical connectives accept as input the output of neurons corresponding to their operands and have activation functions configured to match the connectives' truth functions. Neurons corresponding to propositions accept as input the output of neurons established as proofs of bounds on the propositions' truth values and have activation functions configured to aggregate the tightest such bounds. Bidirectional inference permits every occurrence of each proposition in each formula to be used as a potential proof.

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