Adaptive self-modifying and recombinant systems

• US RE44,968 E1
• Filed: 10/28/2011
• Issued: 06/24/2014
• Est. Priority Date: 11/28/2003
• Status: Active Grant

• Current Assignee: Gula Consulting Limited Liability Company (Intellectual Ventures LLC)
• Original Assignee: World Assets Consulting AG LLC (Intellectual Ventures LLC)
• Inventors: Flinn, Steven Dennis, Moneypenny, Naomi Felina
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US13/284,375
• Time in Patent Office: 970 Days
• Field of Search: 706/12
• US Class Current: 706/12
• CPC Class Codes: N/A

Abstract

An adaptive self-modifying system, a recombinant fuzzy network system, and an adaptive recombinant system are disclosed. The adaptive self-modifying system includes functions and algorithms for the self modification of structural elements, including relationships among system objects of the adaptive self-modifying system, based at least in part on usage behaviors associated with the system. The recombinant and adaptive recombinant systems feature functions for syndicating and combining fuzzy networks. The combining of the structural elements of the adaptive recombinant system may be based, at least in part, on usage behaviors associated with the system, and may be preferentially recombined based on evaluations of network “fitness.”

Claims

1. An adaptive self-modifying system, comprising:

at least one storage device configured to store;

a content aspect comprising information;

a computer-implemented structural aspect comprising the content aspect and associated objects and relationships;

and

a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users;

and

at least one processing device configured to execute a plurality of functions including;

a function that automatically modifies the structural aspect, wherein a modification is based, at least in part, on a plurality of usage behaviors of the one or more users corresponding to a plurality of usage behavior categories; and

a navigation function that enables a user to access the modified structural aspect and that captures usage behaviors associated with the user'"'"'s access of the modified structural aspect.

2. The adaptive self-modifying system of claim 1, wherein the information is selected from a group consisting of text, graphics, audio, video, interactive forms of content, applets, tutorials, courses, demonstrations, advertising content, modules, sections of executable code, and computer programs.

3. The adaptive self-modifying system of claim 1, the usage aspect further comprising one or more usage behaviors, wherein each usage behavior is associated with either a the user, one or more user communities, or a the user and the one or more user communities simultaneously, wherein the user comprises a single-member subset of the one or more users and a community of the one or more user communities comprises a multiple-member subset of the one or more users.

4. The adaptive self-modifying system of claim 1, wherein a the user of the one or more users is selected from a group consisting of a computer-based system, a second adaptive system, and a human being.

5. The adaptive self-modifying system of claim 1, the usage aspect further comprising:

usage behavior categories, wherein the usage behavior categories are selected from a group consisting of navigation and access patterns, collaborative patterns, direct feedback patterns, subscription patterns, self-profiling patterns, reference patterns, and physical location patterns.

6. The adaptive self-modifying system of claim 1, the usage aspect further comprising one or more user communities, wherein the one or more user communities are automatically generated based on usage behaviors.

7. The adaptive self-modifying system of claim 1, wherein an algorithm applies pattern matching of information embodied in the structural aspect and content aspect to produce content interpretation patterns, and associates the content interpretation patterns with usage patterns.

8. The adaptive self-modifying system of claim 1, wherein a the function that automatically modifies the structural aspect comprises:

a function that automatically modifies a structural element, wherein the function that automatically modifies a the structural element is selected from the group consisting of a function to generate a new relationship, a function to modify an existing relationship, a function to delete an existing relationship, a function to add an object, a function to modify an the object, and a function to delete an the object.

9. The adaptive self-modifying system of claim 8, wherein a the function to modify an the object comprises:

a function that automatically modifies an information element of the content aspect.

10. The adaptive self-modifying system of claim 1, wherein a computer-implemented the structural aspect comprising the content aspect and associated objects and relationships comprises:

a fuzzy network structure comprising a plurality of objects, wherein two objects of the plurality of objects have one or more relationships types, and one or more relationships associated with each relationship type, each relationship being uni-directional or bi-directional, and each direction of each relationship has an associated relationship indicator, wherein the relationship indicators associated with each direction are not necessarily the a same magnitude.

11. The adaptive self-modifying system of claim 10, further comprising:

a function that automatically modifies a structural element, wherein the function that automatically modifies a the structural element is selected from the group consisting of a function to generate a new relationship type, a function to generate a new relationship and associated relationship indicators, a function to modify a relationship indicator, a function to add an object, and a function to delete an the object.

12. An adaptive recombinant system, comprising:

at least one storage device configured to store;

a content aspect comprising information;

a computer-implemented structural aspect accessible by a user comprising the content aspect and associated objects and relationships;

a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users; and

at least one processing device configured to execute;

a function that automatically combines a plurality of subsets of the structural aspect, wherein a subset is comprised of a plurality of objects and at least one relationship, and wherein the combining is based, at least in part, on a plurality of usage behaviors of the one or more users corresponding to one or more usage behavior categories.

13. The adaptive recombinant system of claim 12, further comprising:

a syndication function, wherein the syndication function syndicates a structural subset to a destination structural subset.

14. The adaptive recombinant system of claim 12, further comprising:

an object evaluation function.

15. The adaptive recombinant system of claim 12, wherein a computer-implemented the structural aspect accessible by a the user comprising the content aspect and associated objects and relationships comprises:

a fuzzy network structure comprising a plurality of objects, wherein two objects of the plurality of objects have one or more relationships types, and one or more relationships associated with each relationship type, each relationship being uni-directional or bi-directional, and each direction of each relationship has an associated relationship indicator, wherein the relationship indicators associated with each direction are not necessarily the a same magnitude.

16. The adaptive recombinant system of claim 15, further comprising:

a fuzzy network operator function, wherein the fuzzy network operator function is selected from a group consisting of a fuzzy network select function, a fuzzy network union function, a fuzzy network intersection function, a fuzzy network difference function, a fuzzy network complement function, and a fuzzy network resolution function.

17. A recombinant fuzzy network system, comprising:

a first computer-implemented system comprising a structural aspect accessible by a user comprising a first fuzzy network structure, wherein the first fuzzy network structure comprises a plurality of objects, wherein two objects of the first plurality of objects have one or more relationships types, and one or more relationships associated with each relationship type, each relationship being uni-directional or bi-directional, and each direction of each relationship has an associated relationship indicator, wherein the relationship indicators associated with each direction are not necessarily the a same magnitude the content aspect and associated objects and relationships;

and

at least one processing device configured to execute;

a function to select a fuzzy network subset from a second computer-implemented system comprising a second fuzzy network structure, wherein the second fuzzy network structure comprises a second plurality of objects, wherein two objects of the second plurality of objects have one or more second relationships types, each second relationship being uni-directional or bi-directional, and each direction of each second relationship has an associate second relationship indicator, wherein the second relationship indicators associated with each direction are not necessarily the a same magnitude the content aspect and associated objects and relationships, wherein the fuzzy network subset comprises a the second plurality of objects and at least one second relationship;

a function to syndicate the fuzzy network subset to the first computer-implemented system; and

a function to combine the syndicated fuzzy network subsets with a fuzzy network subset of the first computer-implemented system.

18. The recombinant fuzzy network system of claim 17, wherein a the function to combine the syndicated fuzzy network subset with a the fuzzy network subset of the first computer-implemented system comprises:

an object evaluation function.

19. The recombinant fuzzy network system of claim 17, wherein a the function to combine the syndicated fuzzy network subsets with a the fuzzy network subset of the first computer-implemented system comprises:

a fuzzy network operator function, wherein the fuzzy network operator function is selected from a group consisting of, a fuzzy network union function, a fuzzy network intersection function, a fuzzy network difference function, a fuzzy network complement function, and a fuzzy network resolution function.

20. The recombinant fuzzy network system of claim 17, further comprising:

means to evaluate a plurality of fuzzy network structures; and

means to preferentially combine a plurality of fuzzy network structures based on evaluations of the fuzzy network structures.

21. An adaptive self-modifying system, comprising:

at least one storage device configured to store;

a content aspect comprising information;

a structural aspect comprising the content aspect and associated objects and relationships; and

a usage aspect comprising captured usage behaviors, wherein the captured usage behaviors are associated with users; and

at least one processing device configured to execute;

a function that automatically modifies the structural aspect into a modified structural aspect based, at least in part, on the captured usage behaviors of the users and corresponding to a plurality of usage behavior categories; and

a navigation function that enables an additional user to access the modified structural aspect and that captures the captured usage behaviors associated with access by the additional user of the modified computer-implemented structural aspect.

22. The adaptive self-modifying system of claim 21, wherein the information is selected from a group consisting of text, graphics, audio, video, interactive forms of content, applets, tutorials, courses, demonstrations, advertising content, modules, sections of executable code, and computer programs.

23. The adaptive self-modifying system of claim 21, wherein each of the captured usage behaviors is associated with either one of the users, one or more user communities, or one of the users and one or more user communities simultaneously, wherein each of the users comprises a single-member subset of the users and a community of the one or more user communities comprises a multiple-member subset of the users.

24. The adaptive self-modifying system of claim 21, wherein one of the users is selected from a group consisting of a computer-based system, a second adaptive system, and a human being.

25. The adaptive self-modifying system of claim 21, wherein the plurality of usage behavior categories are selected from a group consisting of navigation and access patterns, collaborative patterns, direct feedback patterns, subscription patterns, self-profiling patterns, reference patterns, and physical location patterns.

26. The adaptive self-modifying system of claim 21, wherein one or more user communities are automatically generated based on the captured usage behaviors.

27. The adaptive self-modifying system of claim 21, wherein an algorithm applies pattern matching of the information embodied in the computer-implemented structural aspect and the content aspect to produce content interpretation patterns, and associates the content interpretation patterns with usage patterns.

28. The adaptive self-modifying system of claim 21, wherein the function that automatically modifies the structural aspect comprises a function that automatically modifies a structural element, and the function that automatically modifies the structural element is selected from the group consisting of a function to generate a new relationship, a function to modify an existing relationship, a function to delete the existing relationship, a function to add an object, a function to modify the object, and a function to delete the object.

29. The adaptive self-modifying system of claim 28, wherein the function to modify the object comprises a function that automatically modifies an information element of the content aspect.

30. The adaptive self-modifying system of claim 21, wherein the structural aspect comprises the fuzzy network structure comprising the objects, wherein:

two of the objects have relationships types,

the relationships are associated with the relationship types,

the relationships are uni-directional or bi-directional and have associated relationship indicators, and

the relationship indicators do not necessarily have a same magnitude.

31. The adaptive self-modifying system of claim 30, wherein the function that automatically modifies the structural aspect is selected from a group consisting of a function to generate a new relationship type, a function to generate a new relationship and associated new relationship indicators, a function to modify the relationship indicators, a function to add an additional object, and a function to delete one of the objects.

32. An adaptive recombinant system, comprising:

at least one storage device configured to store;

a content aspect comprising information;

a structural aspect accessible by a user and comprising the content aspect and associated objects and relationships; and

a usage aspect comprising captured usage behaviors, wherein the captured usage behaviors are associated with additional users; and

at least one processing device configured to execute;

a function that automatically combines a plurality of subsets of the structural aspect, wherein the plurality of subsets each comprise a plurality of the objects and at least one of the relationships, and wherein automatically combining the plurality of subsets is based, at least in part, on a plurality of the captured usage behaviors associated with the additional users and corresponding to one or more usage behavior categories.

33. The adaptive recombinant system of claim 32, further comprising a syndication function, wherein the syndication function syndicates a structural one of the plurality of subsets to a destination structural one of the plurality of subsets.

34. The adaptive recombinant system of claim 32, further comprising an evaluation function for the objects.

35. The adaptive recombinant system of claim 32, wherein the structural aspect comprises a fuzzy network structure comprising the objects, wherein:

two of the objects have one or more relationships types,

the relationships are associated with the one or more relationship types,

the relationships are uni-directional or bi-directional and have associated relationship indicators that are not necessarily a same magnitude.

36. The adaptive recombinant system of claim 35, further comprising a fuzzy network operator function selected from a group consisting of a fuzzy network select function, a fuzzy network union function, a fuzzy network intersection function, a fuzzy network difference function, a fuzzy network complement function, and a fuzzy network resolution function.

37. A recombinant fuzzy network system, comprising:

at least one storage device configured to store a first system comprising a structural aspect accessible by a user and comprising a first fuzzy network structure, wherein the first fuzzy network structure comprises a first plurality of objects, two of the first plurality of objects have one or more relationships types, relationships for the first fuzzy network structure are associated with each of the one or more relationship types, and each of the relationships for the first fuzzy network structure are uni-directional or bi-directional and have associated relationship indicators that are not necessarily a same magnitude; and

at least one processing device configured to execute;

a function to select a first fuzzy network subset from a second system comprising a second fuzzy network structure, wherein the second fuzzy network structure comprises a second plurality of objects, two of the second plurality of objects have one or more relationships types, relationships for the second fuzzy network structure are associated with each of the one or more relationship types, each of the relationships for the second fuzzy network structure are uni-directional or bi-directional and have associated relationship indicators that are not necessarily a same magnitude, and wherein the first fuzzy network subset comprises some of the second plurality of objects of the second fuzzy network structure and at least one of the relationships for the second fuzzy network structure;

a function to syndicate the first fuzzy network subset to the first computer-implemented system; and

a function to combine the first fuzzy network subset with a second fuzzy network subset of the first computer-implemented system.

38. The recombinant fuzzy network system of claim 37, wherein the function to combine the first fuzzy network subset with a second fuzzy network subset of the first computer-implemented system comprises an object evaluation function.

39. The recombinant fuzzy network system of claim 37, wherein the function to combine the first fuzzy network subset with a second fuzzy network subset of the first computer-implemented system comprises a fuzzy network operator function, wherein the fuzzy network operator function is selected from a group consisting of, a fuzzy network union function, a fuzzy network intersection function, a fuzzy network difference function, a fuzzy network complement function, and a fuzzy network resolution function.

40. The recombinant fuzzy network system of claim 37, further comprising:

means to evaluate the first fuzzy network structure and the second fuzzy network structure; and

means to preferentially combine the first fuzzy network structure and the second fuzzy network structure based on the evaluation of the first fuzzy network structure and the second fuzzy network structure.