System and techniques for multifactor intelligent agent control are described herein. A history of intelligent agent activity may be received. The history may include a record of intelligent agent activities and corresponding factors used as intelligent agent input to generate the activities. Detail-level-feedback input from a user may also be received. The detail-level-feedback input is the result of a user manipulating a detail-level-feedback user interface that is generic to any factor. An entry-time corresponding to the user manipulation of the detail-level-feedback user interface may be recorded. A set of factors may be identified from the corresponding factors based on a combination of the history of intelligent agent activity and the entry-time. The intelligent agent may be modified by changing an internally represented influence of members of the set of factors on the intelligent agent. The internally represented influence may be changed in accordance with the detail-level-feedback input.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for multifactor intelligent agent control, the system comprising: a history circuit set to obtain a history of intelligent agent activity for an intelligent agent, the history including a record of intelligent agent activities and corresponding factors used as intelligent agent input to generate the activities; a feedback circuit set to obtain: detail-level-feedback input from a user, the detail-level-feedback input resulting from user manipulation of a detail-level-feedback user interface that is generic to any factor; and an entry-time corresponding to the user manipulation of the detail-level-feedback user interface; an identification circuit set to identify a set of factors from the corresponding factors based on a combination of the history of intelligent agent activity and the entry-time; and an adjustment circuit set to modify the intelligent agent by changing an internally represented influence of members of the set of factors on the intelligent agent, the internally represented influence being changed in accordance with the detail-level-feedback input. 2. The system of claim 1, wherein to modify the influence of members of the set of factors includes the adjustment circuit set to adjust a weight of the members in accordance with the detail-level-feedback input. 3. The system of claim 2, wherein to adjust the weight of the members includes the adjustment circuit set to adjust a first weight corresponding to a first member differently than a second weight corresponding to a second member. 4. The system of claim 3, wherein the detail-level-feedback input includes a direction and wherein the first weight is adjusted in the direction and the second weight is not adjusted in the direction. 5. The system of claim 1, wherein to modify the influence of members of the set of factors includes the adjustment circuit set is to adjust an alert threshold of intelligent agent activity in which the members are used by the intelligent agent. 6. The system of claim 1, wherein to identify the set of factors includes the identification circuit set to find input factors used as inputs to the intelligent agent for intelligent agent activity in the history of intelligent agent activity that are within a predetermined time period of the detail-level-feedback input. 7. The system of claim 6, wherein the predetermined time period is different between at least two of the input factors. 8. The system of claim 7, wherein the at least two of the input factors are of different factor types and the predetermined time period is specific to a factor type. 9. A method for multifactor intelligent agent control, the method comprising: receiving a history of intelligent agent activity, the history including a record of intelligent agent activities and corresponding factors used as intelligent agent input to generate the activities; receiving detail-level-feedback input from a user, the detail-level-feedback input resulting from user manipulation of a detail-level-feedback user interface that is generic to any factor, and recording an entry-time corresponding to the user manipulation of the detail-level-feedback user interface; identifying, using a computer system, a set of factors from the corresponding factors based on a combination of the history of intelligent agent activity and the entry-time; and modifying, using the computer system, the intelligent agent by changing an internally represented influence of members of the set of factors on the intelligent agent, the internally represented influence being changed in accordance with the detail-level-feedback input. 10. The method of claim 9, wherein modifying the influence of members of the set of factors includes adjusting a weight of the members in accordance with the detail-level-feedback input. 11. The method of claim 10, wherein adjusting the weight of the members includes adjusting a first weight corresponding to a first member differently than a second weight corresponding to a second member. 12. The method of claim 11, wherein the detail-level-feedback input includes a direction and wherein the first weight is adjusted in the direction and the second weight includes a component that is not in the direction. 13. The method of claim 9, wherein modifying the influence of members of the set of factors includes adjusting an alert threshold of intelligent agent activity in which the members are used by the intelligent agent. 14. The method of claim 9, wherein identifying the set of factors includes finding input factors used as inputs to the intelligent agent for intelligent agent activity in the history of intelligent agent activity that are within a predetermined time period of the detail-level-feedback input. 15. The method of claim 14, wherein the predetermined time period is different between at least two of the input factors. 16. The method of claim 15, wherein the at least two of the input factors are of different factor types and the predetermined time period is specific to a factor type. 17. At least one machine readable medium that is not a transitory propagating signal, the machine readable medium including instruction that, when executed by a machine, cause the machine to perform operations for multifactor intelligent agent control, the operations: receiving a history of intelligent agent activity, the history including a record of intelligent agent activities and corresponding factors used as intelligent agent input to generate the activities; receiving detail-level-feedback input from a user, the detail-level-feedback input resulting from user manipulation of a detail-level-feedback user interface that is generic to any factor, and recording an entry-time corresponding to the user manipulation of the detail-level-feedback user interface; identifying, using a computer system, a set of factors from the corresponding factors based on a combination of the history of intelligent agent activity and the entry-time; and modifying, using the computer system, the intelligent agent by changing an internally represented influence of members of the set of factors on the intelligent agent, the internally represented influence being changed in accordance with the detail-level-feedback input. 18. The at least one machine readable medium of claim 17, wherein modifying the influence of members of the set of factors includes adjusting a weight of the members in accordance with the detail-level-feedback input. 19. The at least one machine readable medium of claim 18, wherein adjusting the weight of the members includes adjusting a first weight corresponding to a first member differently than a second weight corresponding to a second member. 20. The at least one machine readable medium of claim 19, wherein the detail-level-feedback input includes a direction and wherein the first weight is adjusted in the direction and the second weight includes a component that is not in the direction. 21. The at least one machine readable medium of claim 17, wherein modifying the influence of members of the set of factors includes adjusting an alert threshold of intelligent agent activity in which the members are used by the intelligent agent. 22. The at least one machine readable medium of claim 17, wherein identifying the set of factors includes finding input factors used as inputs to the intelligent agent for intelligent agent activity in the history of intelligent agent activity that are within a predetermined time period of the detail-level-feedback input. 23. The at least one machine readable medium of claim 22, wherein the predetermined time period is different between at least two of the input factors. 24. The at least one machine readable medium of claim 23, wherein the at least two of the input factors are of different factor types and the predetermined time period is specific to a factor type.