PROBLEM SOLVING MECHANISM SELECTION FACILITATION APPARATUS AND METHOD

• US 20070288405A1
• Filed: 06/07/2006
• Published: 12/13/2007
• Est. Priority Date: 06/07/2006
• Status: Abandoned Application

• Current Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: Strassner, John C., Menich, Barry J.
• Application Number:
  US11/422,671
• Publication Number:
  US 20070288405A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/041 Abduction

Abstract

An autonomic computational processor can be provided with both at least one substantially closed loop problem solving mechanism (such as, but not necessarily limited to, an abductive algorithm-based problem solving mechanism (101)) and at least one substantially open loop problem solving mechanism (such as, but not necessarily limited to, a machine learning algorithm-based problem solving mechanism (102)). Upon receiving (103) information regarding a problem as relates to a given corresponding process, then, these teachings can provide for automatically determining (104) which of the closed loop and open loop problem solving mechanisms to use to attempt to resolve the problem.

Claims

1. A method comprising:

at an autonomic computational processor;

providing at least one abductive algorithm-based problem solving mechanism;

providing at least one machine learning algorithm-based problem solving mechanism;

receiving information regarding a problem as relates to a process;

automatically determining which of the at least one abductive algorithm-based problem solving mechanism and the at least one machine learning algorithm-based problem solving mechanism to use to attempt to resolve the problem.

2. The method of claim 1 wherein the autonomic computation processor comprises a communications network processor that is arranged and configured to facilitate at least one of network traffic data and network traffic status.

3. The method of claim 1 wherein providing at least one machine learning algorithm-based problem solving mechanism comprises providing a plurality of machine learning algorithm-based problem solving mechanisms.

4. The method of claim 1 wherein the problem relates to at least one of:

an unrecognized process state;

an unrecognized process event.

5. The method of claim 1 wherein receiving information regarding a problem as relates to a process comprises receiving event-based information regarding at least one of process state and process event information.

6. The method of claim 5 wherein receiving information regarding a problem as relates to a process further comprises receiving supplemental information comprising at least one of:

semantical information;

at least one contextual tag.

7. The method of claim 6 wherein automatically determining which of the at least one abductive algorithm-based problem solving mechanism and the at least one machine learning algorithm-based problem solving mechanism to use to attempt to resolve the problem comprises, at least in part, determining whether sufficient supplemental information has been received to facilitate using an abductive algorithm-based problem solving mechanism.

8. The method of claim 7 wherein automatically determining which of the at least one abductive algorithm-based problem solving mechanism and the at least one machine learning algorithm-based problem solving mechanism to use to attempt to resolve the problem further comprises, when sufficient supplemental information has been received to facilitate using an abductive algorithm-based problem solving mechanism, then determining whether a potentially useful abductive algorithm-based problem solving mechanism is available.

15. The autonomic computational processor of claim 4 wherein the problem solving mechanism selector is further configured and arranged to automatically determine which of the at least one abductive algorithm-based problem solving mechanism and the at least one machine learning algorithm-based problem solving mechanism to use to attempt to resolve the problem by, when sufficient supplemental information has been received to facilitate using an abductive algorithm-based problem solving mechanism, then determining whether a potentially useful abductive algorithm-based problem solving mechanism is available.

9. An autonomic computational processor comprising:

at least one abductive algorithm-based problem solving mechanism;

at least one machine learning algorithm-based problem solving mechanism;

a memory having stored therein received information regarding a problem as relates to a process;

a problem solving mechanism selector operably coupled to the memory and being configured and arranged to automatically determine which of the at least one abductive algorithm-based problem solving mechanism and the at least one machine learning algorithm-based problem solving mechanism to use to attempt to resolve the problem.

10. The autonomic computational processor of claim 9 wherein the at least one machine learning algorithm-based problem solving mechanism comprises a plurality of machine learning algorithm-based problem solving mechanisms.

11. The autonomic computational processor of claim 9 wherein the problem relates to at least one of:

an unrecognized process state;

an unrecognized process event.

12. The autonomic computational processor of claim 9 wherein the received information regarding a problem as relates to a process comprises received event-based information regarding at least one of process state and process event information.

13. The autonomic computational processor of claim 12 wherein the received information regarding a problem as relates to a process further comprises received supplemental information comprising at least one of:

semantical information;

at least one contextual tag.

14. The autonomic computational processor of claim 13 wherein the problem solving mechanism selector is further configured and arranged to automatically determine which of the at least one abductive algorithm-based problem solving mechanism and the at least one machine learning algorithm-based problem solving mechanism to use to attempt to resolve the problem by, at least in part, determining whether sufficient supplemental information has been received to facilitate using an abductive algorithm-based problem solving mechanism.

16. A method comprising:

at an autonomic computational processor;

providing at least one substantially closed loop problem solving mechanism;

providing at least one substantially open loop problem solving mechanism;

receiving information regarding a problem as relates to a process;

automatically determining which of the at least one closed loop problem solving mechanism and the at least one substantially open loop problem solving mechanism to use to attempt to resolve the problem.

17. The method of claim 16 wherein the substantially closed loop problem solving mechanism comprises, at least in part, an abductive algorithm-based problem solving mechanism.

18. The method of claim 16 wherein the substantially open loop problem solving mechanism comprises, at least in part, a machine learning algorithm-based problem solving mechanism.

19. The method of claim 16 wherein:

the substantially closed loop problem solving mechanism comprises, at least in part, an abductive algorithm-based problem solving mechanism;

the substantially open loop problem solving mechanism comprises, at least in part, a machine learning algorithm-based problem solving mechanism.