SYSTEMS, APPARATUS, AND METHODS FOR EMBEDDED ENCODINGS OF CONTEXTUAL INFORMATION USING A NEURAL NETWORK WITH VECTOR SPACE MODELING

Systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV) are provided, which includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the of the AV; a pluralit...

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Bibliographic Details
Main Authors Huber, Marcus J, Palanisamy, Praveen
Format Patent
LanguageEnglish
Published 13.02.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROLLING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
REGULATING
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Summary:Systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV) are provided, which includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the of the AV; a plurality of encoded context2vec AV words in a sequence of timing to embed data of context and behavior; a set of inputs which comprise: at least one of a current, a prior, and a subsequent encoded context2vec AV word; a neural network solution applied by the at least one computer to determine a target context2vec AV word of each set of the inputs based on the current context2vec AV word; an output vector computed by the neural network that represents the embedded distributional one-hot scheme of the input encoded context2vec AV word; and a set of behavior control operations for controlling a behavior of the AV.
Bibliography:Application Number: US201816059403