Neuro-symbolic reinforcement learning with first-order logic

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United States of America

PATENT NO 12260328
APP PUB NO 20230108135A1
SERIAL NO

17494055

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Abstract

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A computer-implemented method for reinforcement learning with Logical Neural Networks (LNNs) is provided including receiving a plurality of observation text sentences from a target environment, extracting one or more propositional logic values from the plurality of observation text sentences, finding a class for each propositional logic value by using external knowledge, converting each propositional logic value into a first-order logic by replacing a part in the propositional logic value with a variable word, the part indicating the class, selecting a LNN based on the class among LNNs prepared in advance for each class, each LNN receiving the one or more propositional logic values as a status input and outputting an action with a score indicating a degree of preference for taking the action, and performing a highest score action to the target environment to obtain a next state of the target environment and a reward for the highest score action.

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Patent OwnerAddress
INTERNATIONAL BUSINESS MACHINES CORPORATIONNEW ORCHARD ROAD ARMONK NY 10504

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Chaudhury, Subhajit Kawasaki, JP 20 42
Kimura, Daiki Kanagawa, JP 21 42
Ono, Masaki Tokyo, JP 52 545
Tatsubori, Michiaki Oiso, JP 94 1388

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