Non-disruptive embedding of specialized elements

• US 20060036398A1
• Filed: 01/14/2005
• Published: 02/16/2006
• Est. Priority Date: 07/30/2004
• Status: Active Grant

• Current Assignee: Wei Yen
• Original Assignee: Ikuni, Inc.
• Inventors: Tu, Xiaoyuan, Funge, John, Wright, Ian, Yen, Wei, Dobson, Daniel, Cabral, Brian, McNally, Michael, Duffy, Nigel, Musick, Ron
• Granted Patent: US 7,263,462 B2
• Time in Patent Office: Days
• US Class Current: 702/179
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A system including at least (1) specialized elements that are restricted to a particular domain of data analysis or processing and (2) configurable data that permits the specialized elements to be tailored to a particular application. The configurable data expands applicability of the specialized elements to plural applications within the particular domain. The specialized elements can be provided by a supplier to a developer without the supplier having detailed knowledge of structures and internal operations used by the particular application. The particular application can be generated by the developer without the developer having detailed knowledge of internal operations used by the specialized elements.

Claims

1. A method, including steps of

defining an ontology specifying an application domain;

providing a module capable of being interpreted by a computing device for at least one form of statistical analysis within that ontology;

automatically configuring that module in response to a system that is consistent with that ontology, with the effect of generating an interface between the module and the system, wherein the interface is specified at least in part by the module and at least in part by the sys-tem;

wherein

the system has no substantial requirement for specialized knowledge of that form of statistical analysis; and

the module has no substantial requirement for specialized knowledge of the particular functions provided by the system.

2. A method as in claim 1, wherein that interface provides for exchange of data between the module and the system.

3. A method as in claim 1, wherein that ontology includes a combat model.

4. A method as in claim 1, wherein the module includes a set of derived features responsive to data crossing the interface.

5. A method as in claim 1, wherein the steps of automatically configuring are responsive to at least a portion of code for the system.

6. A method as in claim 1, wherein that ontology includes a model of a game world.

7. A method as in claim 1, wherein that form of statistical analysis includes a form of machine learning.

8. A method as in claim 7, wherein that form of machine learning includes a portion capable of generating a behavior defined within that ontology.

9. A method as in claim 7, including steps of engaging in commerce with respect to rights to at least a portion of that form of statistical analysis.

10. A method as in claim 7, including steps of including that form of statistical analysis in an application program consistent with that ontology.

11. Apparatus including memory or mass storage including instructions, the instructions associated with

steps of defining an ontology specifying an application domain;

steps of providing a module capable of being interpreted by a computing device for at least one form of statistical analysis within that ontology; and

steps of automatically configuring that module in response to a system that is consistent with that ontology, with the effect of generating an interface between the module and the system, wherein the interface is specified at least in part by the module and at least in part by the system;

wherein

the system has no substantial requirement for specialized knowledge of that form of statistical analysis; and

the module has no substantial requirement for specialized knowledge of the particular functions provided by the system.

12. Apparatus as in claim 11, wherein that interface is associated with instructions for exchange of data between the module and the system.

13. A method as in claim 11, wherein that ontology includes a combat model.

14. A method as in claim 11, wherein the module includes a set of derived features responsive to data crossing the interface.

15. A method as in claim 11, wherein the steps of automatically configuring are responsive to one or more instructions associated with the system.

16. A method as in claim 11, wherein that ontology includes a model of a game world.

17. A method as in claim 11, wherein that form of statistical analysis includes a form of machine learning.

18. A method as in claim 17, wherein that form of machine learning includes a portion capable of generating a behavior defined within that ontology.

19. A method as in claim 17, including steps of engaging in commerce with respect to rights to at least a portion of that form of statistical analysis.

20. A method as in claim 17, including steps of including that form of statistical analysis in a set of instructions associated with an application program consistent with that ontology.

21. Apparatus including

means for defining an ontology specifying an application domain;

means for providing a module capable of being interpreted by a computing device for at least one form of statistical analysis within that ontology; and

means for automatically configuring that module in response to a system that is consistent with that ontology, with the effect of generating an interface between the module and the system, wherein the interface is specified at least in part by the module and at least in part by the sys-tem;

wherein

the system has no substantial requirement for specialized knowledge of that form of statistical analysis; and

the module has no substantial requirement for specialized knowledge of the particular functions provided by the system.

22. Apparatus as in claim 21, wherein that interface includes means for exchange of data between the module and the system.

23. A method as in claim 21, wherein that ontology includes a combat model.

24. A method as in claim 21, wherein the module includes a set of derived features responsive to data crossing the interface.

25. A method as in claim 21, wherein the means for automatically configuring are responsive to at least a portion of code for the system.

26. A method as in claim 21, wherein that ontology includes a model of a game world.

27. A method as in claim 21, wherein that form of statistical analysis includes a form of machine learning.

28. A method as in claim 27, wherein that form of machine learning includes means for generating a behavior defined within that ontology.

29. A method as in claim 27, including means for engaging in commerce with respect to rights to at least a portion of that form of statistical analysis.

30. A method as in claim 27, including means for including that form of statistical analysis in an application program consistent with that ontology.

31. A system, including

specialized elements that are restricted to a particular domain of data analysis or processing;

and

configurable data that permits the specialized elements to be tailored to a particular application, thereby expanding applicability of the specialized elements to plural applications within the particular domain.

32. A system as in claim 31, wherein

the specialized elements are provided by a supplier to a developer without the supplier having detailed knowledge of structures and internal operations used by the particular application;

and

the particular application is generated by the developer without the developer having detailed knowledge of internal operations used by the specialized elements.

33. A system as in claim 32, wherein the particular domain is a particular form of game, simulation, or analysis program.

34. A system as in claim 33, wherein the particular form of game, simulation, or analysis program is a battlefield game, simulation, or analysis program.

35. A system as in claim 33, wherein the particular form of game, simulation, or analysis program is a financial game, simulation, or analysis program.

36. A system as in claim 32, wherein the specialized elements enable statistical analysis, data mining, machine learning, online learning, or online analytical processing in the particular domain.

37. A system as in claim 32, wherein the configurable data includes templates of configurable data definitions that, once configured, provide a link between the particular application and the specialized elements.

38. A system as in claim 37, wherein the configurable data includes one or more header files that define structures for features used by the application, whereby the specialized elements can access those features.

39. A system as in claim 37, wherein the configurable data includes one or more parameters that specify predicates and targets for the specialized elements, whereby the specialized elements can respond to queries from the particular application.

40. A system as in claim 37, wherein the configurable data includes

one or more header files that define structures for features used by the application, whereby the specialized elements can access those features;

and

one or more parameters that specify predicates and targets for the specialized elements, whereby the specialized elements can respond to queries from the particular application.

41. A system as in claim 37, wherein

the configurable data is configured at devtime to provide the link between the particular application and the specialized elements;

and

the link is used at runtime to enable the specialized elements to respond to queries from the particular application.

42. A system as in claim 41, wherein the configurable data is provided in one or more flat files, computational graphs, or relational databases generated or modified at devtime and accessed at runtime.

43. A system as in claim 41, wherein at least some of the configurable data is configured through manual editing.

44. A system as in claim 41, wherein at least some of the configurable data is configured through an input interface provided by the supplier along with the specialized elements.

45. A system as in claim 41, wherein a featurizer provided by the supplier is run at devtime to create a linkable library that implements the specialized elements, with the linkable library accessible by the particular application in accordance with the configurable data.

46. A system as in claim 45, wherein the featurizer analyzes dependencies in the configurable data.

47. A system as in claim 45, wherein the particular application links to and uses the linkable library to perform at least one of

marshaling data from the particular application;

modifying models used by the specialized elements in response to the data;

using the models to respond to the queries from the particular application.