KBS - Knowledge Based System

Enhanced Definition

A Knowledge Based System (KBS) on the mainframe is an artificial intelligence application designed to capture, store, and apply human expertise to solve complex problems or make decisions within specific domains. It typically comprises a knowledge base (containing facts and rules) and an inference engine (which applies the rules to the facts). In the z/OS environment, KBS often augments traditional data processing by providing expert reasoning capabilities for tasks that are difficult to automate with conventional programming.

Key Characteristics

- Knowledge Representation: Stores domain-specific knowledge using various formalisms like IF-THEN rules, frames, or semantic networks, often within specialized expert system shells or AI languages.
- Inference Engine: Employs reasoning mechanisms such as forward chaining (data-driven) or backward chaining (goal-driven) to process the knowledge base and derive conclusions.
- Explanation Facility: Can often justify its reasoning process, showing the rules and facts used to reach a particular conclusion, which is crucial for auditing and trust in complex mainframe operations.
- Symbolic Processing: Operates on symbolic representations of knowledge rather than purely numerical data, allowing it to handle qualitative and heuristic information.
- Integration with z/OS Ecosystem: Designed to interact with existing mainframe applications, databases (e.g., DB2, IMS), and data sources (e.g., VSAM, sequential files) through COBOL, PL/I, or Assembler interfaces.
- Domain Specificity: Typically focused on a narrow, well-defined problem domain where human expertise is valuable and can be codified.

Use Cases

- System Diagnostics and Troubleshooting: Automating the diagnosis of complex z/OS system errors, network issues (VTAM), or application failures by applying expert rules to system logs (SMF, SYSLOG) and performance data.
- Configuration Management: Validating proposed changes to complex z/OS configurations (e.g., JES2, RACF rules, CICS definitions) or generating optimal configurations based on operational constraints and best practices.
- Financial Fraud Detection: Analyzing large volumes of transaction data in DB2 or IMS to identify suspicious patterns indicative of fraud, applying expert rules derived from financial analysts.
- Automated Resource Allocation and Scheduling: Optimizing the allocation of mainframe resources (CPU, memory, I/O) or scheduling batch jobs based on dynamic conditions, priorities, and expert knowledge of system behavior.
- Compliance and Regulatory Checking: Ensuring that business processes and data handling within mainframe applications adhere to complex regulatory requirements by applying a codified set of compliance rules.

Related Concepts

KBS is a specialized form of Artificial Intelligence (AI) and Expert Systems that found practical application on the mainframe. It complements traditional Application Development in languages like COBOL and PL/I by providing a declarative, rule-based approach to problem-solving. KBS often relies heavily on Data Management Systems like DB2 and IMS as sources of facts, and its outputs can drive Automation tools or influence Workload Management decisions within z/OS.

Best Practices:

Thorough Knowledge Acquisition: Invest significant effort in systematically acquiring, documenting, and validating the domain expertise from human experts to ensure the knowledge base is accurate and complete.
Modular Design: Structure the knowledge base into modular, manageable components (e.g., rule sets, object classes) to improve maintainability, reduce complexity, and facilitate independent testing.
Validation and Verification: Implement rigorous testing and validation procedures to ensure the KBS produces correct and consistent results, especially when integrated with critical production systems.
Performance Optimization: Design the knowledge base and inference process to minimize resource consumption, considering the high transaction volumes and performance requirements typical of z/OS environments.
Clear Integration Strategy: Define clear interfaces and integration points with existing COBOL applications, JCL procedures, and DB2/IMS databases to ensure seamless operation and data exchange.
Ongoing Maintenance: Establish a process for regularly reviewing and updating the knowledge base to reflect changes in domain expertise, system configurations, or business rules.