Invention Grant
- Patent Title: Generating symbolic domain models from multimodal data
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Application No.: US17035777Application Date: 2020-09-29
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Publication No.: US11645476B2Publication Date: 2023-05-09
- Inventor: Mattia Chiari , Yufang Hou , Hiroshi Kajino , Akihiro Kishimoto , Radu Marinescu
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Michael A. Petrocelli
- Main IPC: G06F40/51
- IPC: G06F40/51 ; G06F40/47 ; G06N3/04 ; G06N3/08

Abstract:
A computer generates a formal planning domain description. The computer receives a first text-based description of a domain in an AI environment. The domain includes an action and an associated attribute, and the description is written in natural language. The computer receives the first text-based description of the domain and extracts a first set of domain actions and associated action attributes. The computer receives audio-visual elements depicting the domain, generates a second text-based description, and extracts a second set of domain actions and associated action attributes. The computer constructs finite state machines corresponding to the extracted actions and attributes. The computer converts the FSMs into a symbolic model, written in a formal planning language, that describes the domain.
Public/Granted literature
- US20220100968A1 GENERATING SYMBOLIC DOMAIN MODELS FROM MULTIMODAL DATA Public/Granted day:2022-03-31
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