Knowledge representation for expert system

• US 5,295,230 A
• Filed: 12/04/1991
• Issued: 03/15/1994
• Est. Priority Date: 12/06/1989
• Status: Expired due to Fees

• Current Assignee: Racal-Datacom, Inc. (Thales SA)
• Original Assignee: Racal-Datacom, Inc. (Thales SA)
• Inventors: Kung, Ching Y.
• Primary Examiner(s): Fleming, Michael R.
• Assistant Examiner(s): Downs, Robert W.
• Application Number:
  US07/802,113
• Time in Patent Office: 832 Days
• Field of Search: 395/75, 395/76, 395/50, 395/12, 395/51, 395/911, 395/912, 395/914, 395/916
• US Class Current: 706/59
• CPC Class Codes: G06F 11/2257 using expert systems
• CPC Class Codes: G06F 11/327 Alarm or error message display
• CPC Class Codes: H04L 41/0631 using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
• CPC Class Codes: H04L 41/0659 by isolating or reconfiguring faulty entities
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 43/00 Arrangements for monitoring or testing data switching networks
• CPC Class Codes: H04L 43/0829 Packet loss
• CPC Class Codes: H04L 43/106 using time related information in packets, e.g. by adding timestamps
• CPC Class Codes: H04L 43/50 Testing arrangements
• CPC Class Codes: Y10S 706/908 Electronic or computer, internal or network, circuit
• CPC Class Codes: Y10S 706/909 Communication
• CPC Class Codes: Y10S 706/911 Nonmedical diagnostics
• CPC Class Codes: Y10S 706/917 Communication

Abstract

An Expert System for providing diagnostics to a data communications network. Expert information is entered using a user friendly User Interface which reduces need for the participation of a Knowledge Engineer. The User Interface including a template for entering a plurality of attributes for a hypothesis tree node. Among the attributes are an identifier for identifying a second node connected to the hypothesis tree node by a branch of a hypothesis tree. If the second node has not been defined, it is added to and displayed in a list of undefined nodes. Once all attributes for a template are completed, an identifier for the hypothesis tree node is added to and displayed in a list of defined nodes.

Claims

1. A method for entering expert information into an expert system residing on a computer, the method comprising in combination the steps of:

said expert system providing to a user a template for entering a plurality of attributes for a hypothesis tree node;

said user defining said hypothesis tree node by entering said attributes of said hypothesis tree node into said template, said attributes including a first identifier for identifying said hypothesis tree node and a second identifier for identifying a second node connected to said hypothesis tree node by a branch of a hypothesis tree;

said expert system automatically adding said first identifier to a list of defined nodes, each of said defined nodes having said attributes defined therefor;

said expert system automatically determining whether or not said second identifier is on said list of defined nodes;

said expert system automatically determining whether or not said second identifier is not on a list of undefined nodes if said second identifier is not on said list of defined nodes, each of said unidentified nodes not having said attributed defined therefor;

said expert system automatically adding said second identifier to said list of undefined nodes if said second identifier is not already on said list of undefined nodes;

said expert system automatically determining whether or not said first identifier is on said list of undefined nodes;

if said first identifier is on said list of undefined nodes, removing said first identifier from said list of undefined nodes; and

said expert system displaying said list of undefined nodes and said list of defined nodes on a screen of said computer.

2. The method of claim 1, further comprising the step of maintaining said list of defined nodes and said list of undefined nodes as stack data structures.

3. An expert system residing on a computer for use with a diagnostic system, comprising in combination:

said diagnostic system including means for providing a plurality of types of alarms;

said expert system including expert knowledge source means for defining a plurality of expert knowledge sources, one of said expert knowledge sources representing expert information for each of said types of alarms, said expert knowledge source means including node adding means for defining at least one of said knowledge sources to have at least a flow-chart node and a hypothesis tree node which points to said flow-chart node;

said attributes of said template for said node being added including;

a node identifier attribute which gives a name to said node being added,

a node type attribute which describes fundamental characteristics of said node being added and which distinguishes between said hypothesis tree type node and said flow-chart type node, and

a points-to attribute which gives the name of another node branching from said node being added.

4. The expert system of claim 3, wherein said node adding means includes means for selecting said node type attribute from a list of node types.

5. The expert system of claim 3, wherein said node adding means is operable for selecting at least one said node type attribute for said hypothesis tree node from a group of:

AND node, OR node and Knowledge Source node.

6. The expert system of claim 3, wherein said node adding means is operable for selecting at least one said node type attribute for said flow-chart tree from a group of:

TEST node, CONCLUSION node, CALL node, CONFIRM node, FACT node, DELAY node and COUNT node.

7. The expert system of claim 3, further comprising means for copying an existing node whereby, addition of new node having attributes in common with said existing node can be accomplished by copying said existing node and modifying attributes which differ from said existing node.

8. The expert system of claim 3, further comprising means for modifying said node type attribute.

9. The expert system of claim 3, further comprising means for modifying said node attributes.

10. The expert system of claim 3,

wherein said alarms from said diagnostic system provide an indication of problems detected by said diagnostic system to be solved by said expert system;

and

an alarm map means for relating types of alarms detected by said diagnostic system to one of said plurality of knowledge sources.

11. The expert system of claim 10, further comprising update means for updating said alarm map means when new knowledge sources or new types of alarms are added to said expert system.

12. The expert system of claim 3, further comprising means for displaying a graphic representation of said knowledge source.

13. The expert system of claim 3, wherein said node adding means further includes:

means for adding said node identifier attribute to a list containing defined nodes, said defined nodes each having said attributes defined therefor;

means for determining whether or not said points-to attribute is on said list of defined nodes;

means for determining whether or not said points-to attribute is not on a list of undefined nodes if said points-to attribute is not on said list of defined nodes, said undefined nodes not having said attributes defined therefor;

means for adding said points-to-attribute to said list of undefined nodes if said points-to-attribute is not already on said list of undefined nodes; and

means for displaying said list of undefined nodes and said list of defined nodes on a screen of said computer.

14. The expert system of claim 3, wherein said one of said expert knowledge sources includes a plurality of hypothesis nodes, said plurality of hypothesis nodes including at least one high level hypothesis node and a plurality of sub-hypothesis nodes, said high level hypothesis points to each of said plurality of sub-hypothesis nodes, one of said sub-hypothesis nodes points to said flow-chart node.

15. The expert system of claim 14, further comprising a second flow-chart node, said first recited flow-chart node points to said second flow-chart node.

16. The expert system of claim 14, wherein each of said sub-hypothesis nodes point to one of a first set of flow chart nodes and at least a portion of said flow chart nodes of said first set point to another flow chart node from a second set of flow chart nodes.