Relationship reasoning engines

• US 10,296,839 B2
• Filed: 08/25/2017
• Issued: 05/21/2019
• Est. Priority Date: 03/22/2011
• Status: Active Grant

• Current Assignee: Nant Holdings IP, LLC (NantWorks, LLC)
• Original Assignee: Patrick Soon-Shiong
• Inventors: Soon-Shiong, Patrick
• Primary Examiner(s): Hill, Stanley K.
• Application Number:
  US15/687,416
• Publication Number:
  US 20170372210A1
• Time in Patent Office: 634 Days
• Field of Search: None
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/025 Extracting rules from data
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/041 Abduction
• CPC Class Codes: G06N 5/043 Distributed expert systems; Blackboards
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06T 9/00 Image coding bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00
• CPC Class Codes: G06V 20/00 Scenes; Scene-specific elements control of digital cameras H04N23/60
• CPC Class Codes: G16H 20/00 ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

A reasoning engine is disclosed. Contemplated reasoning engines acquire data relating to one or more aspects of various environments. Inference engines within the reasoning engines review the acquire data, historical or current, to generate one or more hypotheses about how the aspects of the environments might be correlated, if at all. The reasoning engine can attempt to validate the hypotheses through controlling acquisition of the environment data.

Claims

1. A computer-based relational reasoning engine comprising:

an inquiry interface configured to receive an inquiry over a network;

a database containing relational knowledge and configured to store data objects, wherein each one of the data objects has data object attributes; and

at least one server coupled with the inquiry interface and that is, upon execution of software instructions stored in a non-transitory computer readable memory by at least one processor, configurable to;

receive, via the inquiry interface, the inquiry, wherein the inquiry relates to a relationship between objects of a set of objects;

search the database for data objects related to objects in the set of objects;

select one or more reasoning rules sets from a plurality of reasoning rules sets as a function of data object attributes of the data objects related to objects in the set of objects;

generate a plurality of hypotheses with respect to relations between at least one pair of objects of the set of objects as a function of the one or more reasoning rules sets related to the data object attributes of the data objects related to the objects in the set of objects and as a function of an inference with respect to relations between the set of data objects; and

configure a computing device to present a response to the inquiry, wherein the response is based on at least one hypothesis of the plurality of hypotheses.

2. The engine of claim 1, wherein the at least one hypothesis relates to a physical relationship between the at least one pair of objects in the set of objects.

3. The engine of claim 1, wherein the at least one hypothesis relates to a behavior of the set of objects over time.

4. The engine of claim 1, wherein the at least one hypothesis relates to a behavior of a moving object over time.

5. The engine of claim 1, wherein the at least one hypothesis relates to a relative position of one object of the set of objects with respect to another object of the set of objects.

6. The engine of claim 1, wherein the at least one hypothesis relates to a relationship between different mental representations.

7. The engine of claim 1, wherein the at least one hypothesis is based on a context of an environment.

8. The engine of claim 1, wherein the at least one hypothesis relates to a derived relationship.

9. The engine of claim 1, wherein the plurality of hypotheses is generated based on a priori knowledge.

10. The engine of claim 1, wherein the plurality of hypotheses is generated based on a previously generated hypothesis.

11. The engine of claim 1, wherein the set of objects comprises one or more physical objects, virtual objects, or 3D-rendered objects.

12. The engine of claim 1, wherein the set of objects comprises a moving object.

13. The engine of claim 1, wherein the set of objects comprises one or more events.

14. The engine of claim 1, wherein the inquiry comprises a relational attribute.

15. The engine of claim 1, wherein the inquiry comprises at least one relational attribute and at least one non-relational attribute.

16. The engine of claim 1, wherein the inquiry comprises at least one of text data, audio data, image data, video data, and sensor data.

17. The engine of claim 1, wherein the at least one server comprises a cloud-based service.

18. The engine of claim 1, wherein the at least one server is further configurable to request, via the inquiry interface, updated data associated with the plurality of hypotheses and according to a validation plan.

19. The engine of claim 1, wherein the at least one server is further configurable to change the plurality of hypotheses as a function of updates to the related data objects.

20. The engine of claim 1, wherein the inquiry interface comprises a mobile device interface.

21. The engine of claim 20, wherein the mobile device interface comprises at least one of a mobile phone, a portable computer, and a computing tablet.

22. The engine of claim 1, wherein the data objects include at least one of visual data, text-based data, video data, identity data, demographic data, and sensor data.

23. The engine of claim 1, wherein the data objects comprise an observed change in an object of a set of objects.

24. The engine of claim 1, wherein the presentation includes reasons or additional information supporting the at least one hypothesis.

25. The engine of claim 24, wherein the reasons include a type of reasoning or reason steps supporting the at least one hypothesis.

26. The engine of claim 25, wherein the type of reasoning includes at least one of deductive reasoning, adductive reasoning, inductive reasoning, amplitative reasoning, case-based reasoning, metaphorical mapping, forward chaining reasoning, backward chaining reasoning, analogical reasoning, cause-and-effect reasoning, defeasible or indefeasible reasoning, comparative reasoning, conditional reasoning, decompositional reasoning, exemplar reasoning, modal logic, set-base reasoning, systemic reasoning, syllogistic reasoning, probabilistic reasoning, and paraconsistent reasoning.

27. The engine of claim 1, wherein the presentation comprises a web page within a browser operating on the computing device.

28. The engine of claim 1, wherein the at least one server generates the plurality of hypotheses in real-time relative to changes in the data objects.