• Source: VP-Expert
    • VP-Expert is an artificial intelligence development tool that gained popularity in the 1980s and 1990s. Published by Paperback Software, VP-Expert was designed to facilitate the creation of rule-based expert systems, primarily for applications in business and industry. VP-Expert was created by Brian Sawyer.
      VP-Expert quickly gained market share in the expert system development tool sector, particularly in academic and small to medium-sized business environments. By 1990, it had become the best-selling expert system shell, with 120,000 copies sold worldwide and site licenses at DuPont, Kodak, and the Wharton School of Business.


      Background


      VP-Expert emerged during a period of significant activity surrounding artificial intelligence, particularly expert systems. Expert systems aimed to capture and replicate human expertise in specific domains, enabling computers to solve problems, make decisions, and provide advice in a manner similar to human experts. This period saw the development of various expert system shells, software tools designed to facilitate the creation of expert systems without requiring extensive programming knowledge.
      The appeal of VP-Expert lay in its relative ease of use and affordability. It offered a user-friendly interface and a rule-based approach that was intuitive for many users, particularly those with a background in business or logic.


      Features


      VP-Expert incorporated several features that supported the development and deployment of expert systems:

      Rule-Based Reasoning: VP-Expert utilized a rule-based inference engine to process knowledge represented as IF-THEN rules.
      Backward Chaining: The system primarily employed backward chaining, a goal-driven reasoning strategy, to deduce conclusions or solutions based on the given facts and rules.
      User Interface: VP-Expert offered a user-friendly interface for knowledge acquisition, simplifying the process of defining rules, facts, and goals.
      Explanation Facility: The system was capable of providing explanations for its reasoning, enhancing user understanding of how conclusions were reached.


      Applications


      VP-Expert found applications across various domains, including:
      Engineering and Aviation:

      Environmental Analysis: Researchers used VP-Expert to develop a knowledge-based system for analyzing the impact of particulate matter air pollution on human health.
      Engineering Design: VP-Expert was utilized in the creation of a prototype expert system to assist in fishway design.
      Aviation Management: The tool was employed to develop an expert system aimed at maximizing airport capacity while adhering to noise-mitigation plans.
      Business and Finance:

      Loan Approval: Banks and financial institutions utilized VP-Expert to build expert systems for evaluating loan applications. These systems assessed creditworthiness, analyzed financial statements, and determined loan eligibility based on predefined rules and risk factors, streamlining the loan approval process.
      Investment Portfolio Management: VP-Expert was used to develop systems that provided investment advice based on market trends, economic indicators, and investor preferences. These systems helped users make informed investment decisions and manage their portfolios effectively.
      Fraud Detection: VP-Expert was employed in the financial sector to develop systems for detecting fraudulent activities like credit card fraud and insurance claims fraud. These systems analyzed transaction patterns and identified anomalies, helping prevent financial losses.
      Healthcare:

      Medical Diagnosis: Although not as widely used as specialized medical expert systems, VP-Expert was explored for developing diagnostic support tools. These systems could analyze patient symptoms, medical history, and test results to assist physicians in identifying potential illnesses and recommending treatment options.
      Nursing Care: VP-Expert was used to create systems that provided guidance to nurses on patient care, such as determining appropriate medication dosages, managing wound care, and monitoring vital signs. These systems helped standardize care and improve patient outcomes.


      Limitations


      While VP-Expert offered certain advantages, it also had limitations:

      Scalability: Its rule-based approach could become challenging to manage for large and complex knowledge bases.
      Knowledge Acquisition Bottleneck: The process of eliciting and encoding knowledge from experts could be time-consuming and difficult.


      References

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