Telephone with intuitive capability

• US 7,974,935 B2
• Filed: 12/05/2008
• Issued: 07/05/2011
• Est. Priority Date: 06/26/2001
• Status: Expired due to Fees

• Current Assignee: Arif M. Ansari, Yusuf Sulaiman M. Shiek Ansari
• Original Assignee: Arif M. Ansari, Yusuf Sulaiman M. Shiek Ansari
• Inventors: Ansari, Arif M, Shiek Ansari, Yusuf Sulaiman M
• Primary Examiner(s): Holmes; Michael B
• Assistant Examiner(s): Wong; Lut
• Application Number:
  US12/329,417
• Publication Number:
  US 20090083199A1
• Time in Patent Office: 942 Days
• Field of Search: 706/12
• US Class Current: 706/12
• CPC Class Codes: A63F 13/10 Control of the course of the game, e.g. start, progess, end
• CPC Class Codes: A63F 13/12 involving interaction between a plurality of game devices, e.g. transmisison or distribution systems protocols for networked virtual reality, networked games H04L29/06034
• CPC Class Codes: A63F 13/23 for interfacing with the game device, e.g. specific interfaces between game controller and console
• CPC Class Codes: A63F 13/30 Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
• CPC Class Codes: A63F 13/338 using television networks
• CPC Class Codes: A63F 13/45 Controlling the progress of the video game
• CPC Class Codes: A63F 13/67 adaptively or by learning from player actions, e.g. skill level adjustment or by storing successful combat sequences for re-use
• CPC Class Codes: A63F 13/798 for assessing skills or for ranking players, e.g. for generating a hall of fame computing the game score A63F13/46
• CPC Class Codes: A63F 2300/558 by assessing the players' skills or ranking
• CPC Class Codes: A63F 2300/6027 using adaptive systems learning from user actions, e.g. for skill level adjustment
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/443 OS processes, e.g. booting an STB, implementing a Java virtual machine in an STB or power management in an STB
• CPC Class Codes: H04N 21/466 Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4751 for defining user accounts, e.g. accounts for children

Abstract

A processing device and a method of providing learning capability thereto are provided. A list containing a plurality of listed items with an associated item probability distribution is generated. The item probability distribution comprises a plurality of probability values corresponding to the plurality of listed items. One or more items are selected from the plurality of listed items based on the item probability distribution, a performance index indicative of a performance of the processing device relative to the objective is determined, and the item probability distribution is modified based on the performance index.

Claims

1. A method of providing learning capability to a telephone having an objective of learning favorite phone numbers, comprising:

generating a list containing a plurality of listed phone numbers with an associated phone number probability distribution comprising a plurality of probability values corresponding to said plurality of listed phone numbers;

selecting one or more phone numbers from said plurality of listed phone numbers based on said phone number probability distribution;

determining a performance index indicative of a performance of said phone relative to said objective; and

modifying said phone number probability distribution using a learning automaton based on said performance index.

2. The method of claim 1, further comprising:

identifying a phone number associated with a phone call; and

determining if said identified phone number matches any listed phone number contained in said list, wherein said performance index is derived from said matching determination.

3. The method of claim 2, wherein said phone number probability distribution is modified by updating it if said identified phone number matches said any listed phone number.

4. The method of claim 3, wherein said phone number probability distribution update comprises a reward-inaction update.

5. The method of claim 4, wherein a corresponding probability value is rewarded if said identified phone number matches said any listed phone number.

6. The method of claim 3, further comprising adding a phone number corresponding to said identified phone number to said list if said identified phone number does not match said any listed phone number, wherein said phone number probability distribution is modified by adding a probability value corresponding to said added phone number to said phone number probability distribution.

7. The method of claim 6, wherein another phone number on said list is replaced with said added phone number, and another probability value corresponding to said replaced listed phone number is replaced with said added probability value.

8. The method of claim 2, wherein said phone number probability distribution is modified by updating it only if said identified phone number matches phone number within said selected one or more phone numbers.

9. The method of claim 8, wherein said phone number probability distribution update comprises a reward-inaction update.

10. The method of claim 9, wherein a corresponding probability value is rewarded if said identified phone number matches said any listed phone number.

11. The method of claim 8, wherein said phone number probability distribution is modified by increasing a corresponding probability value if said identified phone number matches a listed phone number that does not correspond to phone number in said selected one or more phone numbers.

12. The method of claim 8, further comprising adding a phone number corresponding to said identified phone number to said list if said identified phone number does not match said any listed phone number, wherein said phone number probability distribution is modified by adding a probability value corresponding to said added phone number to said phone number probability distribution.

13. The method of claim 12, wherein another phone number on said list is replaced with said added phone number, and another probability value corresponding to said replaced listed phone number is replaced with said added probability value.

14. The method of claim 1, wherein said selected one or more phone numbers corresponds to the highest one or more probability values in said phone number probability distribution.

15. The method of claim 1, further comprising placing said plurality of listed phone numbers in an order according to corresponding probability values.

16. The method of claim 1, wherein said phone number probability distribution is modified by increasing a probability value.

17. The method of claim 1, wherein said phone number probability distribution is modified by adding a probability value.

18. The method of claim 17, wherein said phone number probability distribution is modified by replacing a probability value with said added probability value.

19. The method of claim 1, further comprising:

generating another list containing another plurality of listed phone numbers with another associated phone number probability distribution comprising another plurality of probability values corresponding to said other plurality of listed phone numbers; and

selecting another one or more phone numbers from said other plurality of phone numbers based on said other phone number probability distribution.

20. The method of claim 19, further comprising:

identifying a phone number associated with a phone call;

determining if said identified phone number matches any listed phone number contained in said list;

identifying another phone number associated with another phone call; and

determining if said other identified phone number matches any listed phone number contained in said other list;

wherein said performance index is derived from said matching determinations.

21. The method of claim 19, further comprising:

identifying a phone number associated with a phone call;

determining current temporal information;

selecting one of said list and said other list based on said current temporal information determination; and

determining if said identified phone number matches any listed phone number contained in said selected list,

wherein said performance index is derived from said determination.

22. The method of claim 21, wherein said temporal information is a day of the week.

23. The method of claim 21, wherein said temporal information is a time of the day.

24. The method of claim 1, wherein said list is one of a plurality of phone number lists corresponding to a plurality of users, the method further comprising determining which user performed said identified phone number, wherein said list corresponds with said determined user.

25. The method of claim 24, wherein said user determination is based on the operation of one of a plurality of keys associated with said processing device telephone.

26. A telephone, comprising:

a phone number selection module configured for selecting one or more of a plurality of favorite phone numbers from a plurality of phone numbers contained in a list, said selection being based on a phone number probability distribution comprising a plurality of probability values corresponding to said plurality of listed phone numbers;

an outcome evaluation module configured for determining if an identified phone number associated with a phone call matches any listed phone number contained in said list; and

a probability update module configured for updating said action probability distribution using a learning automaton; and

an intuition module configured for modifying a functionality of said probabilistic learning module based on said matching determination.

27. The telephone of claim 26, wherein said one or more favorite phone numbers correspond to one or more of the highest probability values in said phone number probability distribution.

28. The telephone of claim 26, wherein said phone number selection module is further configured for placing said plurality of listed phone numbers in an order according to corresponding probability values.

29. The telephone of claim 26, wherein said intuition module is configured for modifying said probability update module by directing it to update said phone number probability distribution if said identified phone number matches said any listed phone number.

30. The telephone of claim 29, wherein said probability update module is configured for updating said phone number probability distribution using a reward-inaction algorithm.

31. The telephone of claim 30, wherein said probability update module is configured for rewarding a corresponding probability value.

32. The telephone of claim 29, wherein said intuition module is configured for modifying said probability update module by adding a phone number corresponding to said identified phone number to said list and adding a probability value corresponding to said added phone number to said phone number probability distribution if said identified phone number does not match said any listed phone number.

33. The telephone of claim 32, wherein another phone number on said list is replaced with said added phone number, and another probability value corresponding to said replaced listed phone number is replaced with said added probability value.

34. The telephone of claim 26, wherein said intuition module is configured for modifying said probability update module by directing it to update said phone number probability distribution only if said identified phone number matches a listed phone number corresponding to one of said favorite phone numbers.

35. The telephone of claim 34, wherein said probability update module is configured for updating said phone number probability distribution using a reward-inaction algorithm.

36. The telephone of claim 35, wherein said probability update module is configured for rewarding a corresponding probability value.

37. The telephone of claim 34, wherein said intuition module is configured for modifying said probability update module by increasing a corresponding probability value if said identified phone number matches a listed phone number that does not correspond to one of said one or more favorite phone numbers.

38. The telephone of claim 34, wherein said intuition module is configured for modifying said probability update module by adding a phone number corresponding to said identified phone number to said list and adding a probability value corresponding to said added phone number to said phone number probability distribution if said identified phone number does not match said any listed phone number.

39. The telephone of claim 38, wherein another phone number on said list is replaced with said added phone number, and another probability value corresponding to said replaced listed phone number is replaced with said added probability value.

40. The telephone of claim 26, further comprising a favorite phone number function key the operation of which prompts said phone number selection module to select said one or more phone numbers.

41. The telephone of claim 26, wherein said list is one of a plurality of lists corresponding to a plurality of users, and said phone number selection module is further configured for determining which user performed said identified phone number, wherein said list corresponds with said determined user.

42. The telephone of claim 41, further comprising a plurality of user function keys, wherein said user determination is based on the operation of one of said plurality of user function keys.