Expert Systems Development Stages

Expert System Development Stages

• Expert systems development progresses through a structured sequence of stages, encompassing various tasks and activities.
• Five key stages are identified: task analysis, knowledge acquisition, prototype development, expansion and refinement, and verification and validation.

Types of Computerized Systems

• Data Processing Systems (DPS) focus on utilizing existing computer systems to execute standard business tasks.
• Management Information Systems (MIS) concentrate on supporting managerial decision-making processes by leveraging existing computer databases, reports, and supplementary information systems.
• Decision Support Systems (DSS) aim to assist managers in making informed decisions by providing a platform for interaction, crucial information gathering, and an analysis of the decision-making process.
• Knowledge-based Systems (KBS) are diverse in their development situations, handling a wide range of unique conditions.

Knowledge Engineering

• Knowledge engineering involves acquiring, organizing, and analyzing knowledge to address specific problems.
• This process of building expert systems directly entails knowledge engineering.
• It tackles the complexity of developing skilled computer systems by first extracting and organizing expert knowledge for an effective implementation.
• A key aspect is manipulating large amounts of expert heuristic knowledge into a usable format for computer programs to solve complex issues.

Components of Expert System Development

• This illustrates the sequential steps involved in the creation of an expert system.
• Experts are the primary source of knowledge for the systems.
• Knowledge and data are acquired and organized.
• Inference engines process and evaluate the data to guide the decision-making process.
• An interface facilitates interactions between users and the system.

Human Elements

• Domain Experts possess in-depth knowledge and expertise to resolve specific problems in a particular area.
• Knowledge Engineers design, develop, and test expert systems.
• End-Users are the individuals who interact and make use of the developed system.

Qualifications for Human Elements

• Expert knowledge and problem-solving skills are crucial for domain experts; clear communication of their expertise, including substantial time allocations, is essential.
• Knowledge engineers need proficiency in knowledge engineering, excellent communication, and the ability to effectively align issues with the system's capabilities to ensure the system meets expected requirements.
• End-users play an essential role in the design and development of the interface, assisting with knowledge acquisition, and the support development aspect of the system.

Activity of Knowledge Engineering

• Knowledge engineers employ principles and tools from AI research to tackle complex practical problems.
• They identify challenges related to capturing, representing, and effectively utilizing expert knowledge pertinent to systems' capabilities.
• Creating and describing "lines of reasoning" is a core aspect of building knowledge-based systems.
• Knowledge engineering is a unique form of programming that focuses on constructing intricate computer programs utilizing problem-solving knowledge.

Expert System Development Stages (Continued)

• Task analysis, a crucial initial stage, involves identifying a problem area, defining its scope, and determining resource needs (e.g., personnel, time, computing resources).
• Knowledge acquisition involves extracting problem-solving expertise from domain experts and converting it into a suitable format for the computer system. This critical phase is often the most arduous.
• Prototype development involves creating an initial working version of the expert system that uses the organized knowledge base.
• Expansion and refinement entail enlarging and improving the initial system's knowledge base and capabilities.
• Verification and validation involve testing the system's functionality and accuracy to ensure it attains high standards of performance as defined by domain experts.

Expert Systems Evolution

• Expert systems increasingly handle progressively challenging tasks while simultaneously refining their knowledge representation methods.
• More complex systems are usually more challenging to develop.
• Integration with conventional systems is a common practice for knowledge-based systems (KBS).

Conclusions to ES Development

• A deep understanding of the domain, crucial thinking and communication skills are essential for knowledge engineers.
• Skill sets such as interpersonal interaction and emotional intelligence skills are paramount for efficient information extraction.
• User interface design is also key, and requires meticulous attention; this is important for successful implementation.
• The input of domain experts is often crucial for the system's development, refining its performance to established standards of excellence.

Skills Useful in ES Development

• Essential skills for successful development include:
  • Strong analytical and problem-solving skills
  • Effective communication and interpersonal skills
  • Comprehensive computer proficiency, especially in areas relevant to the system's scope.

Thinking Skills

• Conceptualization—reformulation and organization of knowledge for effective computerization is crucial for development success.
• Inferential reasoning—making useful inferences from collected information—is also vital.
• Heuristics—problem-solving strategies.

Individual Interpersonal & Organizational Behavior Skills

• Essential elements in all stages of development, including knowledge acquisition, user engagement, and internal team processes.
• Excellent communication and interpersonal skills are necessary to successfully interact with stakeholders.
• Interviewing skills and emotional intelligence are critical.
• Leadership and motivation play integral roles.

Computer Expertise Skills

• While essential in some larger cases, comprehensive computer skills are not always absolutely necessary in all expert system development.
• The majority of the effort usually prioritizes other facets, such as domain information and user interaction.