Expert Systems – An Area of Artificial intelligence Download AI UOS CS3811 Slides


Expert Systems are special research area of Artificial intelligence. These slides on Expert System in the form of PDF format are made and published for the students computer sciences and Information technology  of undergraduate level. Student may download for study reference. Almost in all universities Artificial intelligence is being taught in CS and IT discipline in last year of the classes. Expert system history started from 1965. A lot of research material can be found in expert systems journal about the use of expert systems in agriculture, healthcare, finance and commerce.

Brief summary of the Lecture slides

Expert systems are mainly divided into three main parts, Knowledge base, Inference rules and user interface. Knowledge base are created by knowledge engineers. Inference rules are defined with the help of forward and backward chaining. In the end advantages, disadvantages and list of examples of expert systems are discussed.

These slides will cover following key topics about expert systems.

  • History of Expert system
  • Characteristics of ES
  • Knowledge Engineering
  • Knowledge Acquisition
  • Classical ES
  • Case-Based Reasoning
  • expert system applications
  • expert system example
  • components of expert system
  • list of expert systems
  • rule based expert system
  • advantages of expert system  
  • limitations of expert system

Click to Download Expert System Slides

Author: Habibullah Qamar

Its me Habib Ullah Qamar working as a Lecturer (Computer Sciences) in Pakistan. I have an MS(M.Phil) degree in computer sciences with specialization in software engineering from Virtual University of Pakistan Lahore. I have an experience of more than 15 years in the filed of Computer Science as a teacher. Blog Writing is my passion. I have many blogs, This one is special made with the aim of providing 100% Free online coaching and training to the students of under-graduate and postgraduate classes. Most of the students enrolled in computer sciences, information technology, software engineering and related disciplines find it difficult to understand core concepts of programming and office automation. They find difficult in understanding and solving their assignments.