公开(公告)号：US20230281349A1

公开(公告)日：2023-09-07

申请号：US17687535

申请日：2022-03-04

Applicant: AUTODESK, INC.

Inventor： Yi WANG ,  Mehdi NOURBAKHSH ,  Dale ZHAO

IPC: G06F30/13 ,  G06F30/12

CPC classification number: G06F30/13 ,  G06F30/12

Abstract: In various embodiments, an intent-driven layout application automatically generates design for floor spaces. The intent-driven layout application generates a logic formula based on a statement of a design intent and at least one fuzzy geometric predicate. The intent-driven layout application computes, for a first spatial object, a set of desirability values for a set of candidate placements within a first design based on the logic formula. Based on the set of desirability values, the intent-driven layout application selects a first candidate placement from the set of candidate placements. Subsequently, the intent-driven layout application generates a second design based on the first design, where the first spatial object has the first candidate placement within the second design.

公开(公告)号：US20220083703A1

公开(公告)日：2022-03-17

申请号：US17071992

申请日：2020-10-15

Applicant: AUTODESK, INC.

Inventor： Yi WANG ,  Mehdi NOURBAKHSH

IPC: G06F30/13 ,  G06N20/00 ,  G06F30/27

Abstract: One embodiment of the present invention sets forth a technique for performing machine learning. The technique includes applying one or more placement rules to a floorplan of a building to generate a set of candidate column locations in the floorplan. The technique also includes selecting, using a first reinforcement learning (RL) agent, one or more column locations from the set of candidate column locations based on a structural stability of the one or more column locations. The technique further includes outputting the floorplan that includes the one or more column locations as a structural design for the building.

公开(公告)号：US20240202381A1

公开(公告)日：2024-06-20

申请号：US18595179

申请日：2024-03-04

Applicant: AUTODESK, INC.

Inventor： Yi WANG ,  Medhi NOURBAKHSH

IPC: G06F30/13 ,  G06F30/27 ,  G06N20/00

CPC classification number: G06F30/13 ,  G06F30/27 ,  G06N20/00

Abstract: One embodiment of the present invention sets forth a technique for performing machine learning. The technique includes applying one or more placement rules to a floorplan of a building to generate a set of candidate column locations in the floorplan. The technique also includes selecting, using a first reinforcement learning (RL) agent, one or more column locations from the set of candidate column locations based on a structural stability of the one or more column locations. The technique further includes outputting the floorplan that includes the one or more column locations as a structural design for the building.