公开(公告)号：US20230312132A1

公开(公告)日：2023-10-05

申请号：US17928251

申请日：2021-06-01

Applicant: THALES

Inventor： Aurélien THIRIET ,  Jaime DIAZ PINEDA ,  Daniel HAURET

IPC: B64D47/00 ,  G06F40/35 ,  G06N3/086 ,  G06N3/042 ,  G06N3/043 ,  G05B13/02

CPC classification number: B64D47/00 ,  G06F40/35 ,  G06N3/086 ,  G06N3/042 ,  G06N3/043 ,  G05B13/0285

Abstract: Systems and methods for improved human-machine dialog, include bidirectional translations notably through the translation of commands by the human into a form able to be manipulated by the machine, and conversely of results produced by the machine into a form intelligible to the human. Some developments describe notably the display of portions of intermediate reasoning followed by the machine (for example explanation of root causes).

公开(公告)号：US20240104406A1

公开(公告)日：2024-03-28

申请号：US18470418

申请日：2023-09-20

Applicant: THALES

Inventor： Thomak LEDUC ,  Jaime DIAZ PINEDA ,  Maelle ANDRICQUE

IPC: G06N5/025

CPC classification number: G06N5/025

Abstract: A method includes providing logical rules each associating a piece of knowledge with a physical datum or data, analyzing the provided logical rules in order to extract a set of knowledge and a set of physical data; developing a network of logical tensors including a neural network for each piece of knowledge and a neural network for each physical datum, a neural network calculating a relevance of the piece of knowledge or of the associated physical datum from a current situation, defined by the current values of the physical data, training the network on a learning database, and executing the decision-making aid algorithm resulting from the learning phase on a new situation, in order to calculate the relevance of each piece of knowledge and each physical datum with respect to the new situation.