METHOD AND SYSTEM FOR DATA PROCESSING SYSTEM ERROR DIAGNOSIS UTILIZING HIERARCHICAL BLACKBOARD DIAGNOSTIC SESSIONS

Patent №

US 5,448,722

Granted

1995-09-05

Filed 1993

Owner

INTERNATIONAL BUSINESS MACHINES CORPORATION

AI components

1

planning

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

08029072

A method and system in a data processing system for managing a hierarchical error diagnostic system having a plurality of diagnostic modules for diagnosing a component failure within a target system having a predetermined group of components within each of a plurality of hierarchical levels. After the identification of selected hierarchical levels within the target system, and identification of the components within each hierarchical level, a first blackboard data storage area is initialized for utilization during a diagnostic session. Thereafter, a diagnostic analysis of a first predetermined group of components within a first selected hierarchical level is initiated. The diagnostic analysis utilizes the first blackboard data storage area and multiple diagnostic modules assigned to diagnose the components within the first selected hierarchical level. Upon conclusion of the diagnostic analysis, a diagnostic result is determined from selected information learned during the first diagnostic analysis. In preparation for a second diagnostic analysis of a second group of components in a second hierarchical level, which were selected in response to a result from the initial diagnostic analysis, a second blackboard data storage area is initialized utilizing selected information learned from the initial diagnostic analysis. Thereafter, a second diagnostic analysis of a second predetermined group of components within a second selected hierarchical level is automatically initiated. The second diagnostic analysis utilizes selected information learned during the initial diagnostic session, which is stored within the second blackboard data storage area during initialization, and multiple diagnostic modules within the second selected hierarchical level.

AI classification

Planning1.00
Knowledge representation0.14
AI hardware0.05
Vision0.05
Machine learning0.01
Natural language0.00
Evolutionary computation0.00
Speech0.00

Ownership

INTERNATIONAL BUSINESS MACHINES CORPORATION

assignment · 64550668

Assignors

LYNNE, KENTON J., SAMRA, NICHOLAS, WALKER, THOMAS M.

On an employer assignment, the assignors are typically the inventors.

From the same owner

© 2026 NYSGPT2525 LLC