Computer Science 456: Artificial Intelligence and Expert Systems

Unit 7: Expert Systems and Problem Solving

Problem solving is the driving force behind developing methods and techniques for capturing and representing intelligence. In previous units we have discussed different knowledge representations and reasoning techniques, and algorithms used for implementing problem solvers. This unit focuses on strong methods for problem solvers that use a large amount of domain-specific knowledge. Rule-based systems and especially expert systems are covered in this unit as the main examples of strong methods. Techniques for implementing other strong methods, such as case-based reasoning and planning are also presented.

Activities

Project

Start working on the project, and contact your tutor to discuss any issue you have with this unit or the project.

Section 7.1: Expert Systems

This section describes rule-based systems and discusses the architecture of expert systems. The knowledge-engineering process, reasoning process, and control process in expert systems are discussed.

Learning Objectives

  • Describe the architecture of expert systems.
  • Discuss the process for knowledge acquisition and knowledge engineering.
  • Outline the development process of rule-based expert systems.
  • Contrast the goal-driven and data-driven reasoning processes.
  • Discuss the control mechanisms in expert systems.

Key Terms

strong method problem solving, expert system, knowledge base, inference engine, knowledge engineering, conceptual model, goal-driven reasoning, data-driven reasoning

Readings

Read the sections “Introduction,” “Overview of Expert System Technology,” and “Rule-Based Expert Systems” from Chapter 8, Strong Method Problem Solving.

Tasks

Practice the following exercises from Chapter 8 of the textbook:

  •  Exercises 1, 2, and 3. You may want to use the Personal Workspace wiki on the course home page and/or share your observations with classmates in the COMP 456 General Discussion forum.

Section 7.2: Other Models for Problem Solving

This section discusses other strong methods for problem solving. Using examples, it presents the main concepts of the model-based reasoning system and the case-based reasoning system. It discusses hybrid systems that are implemented using a combination of different methods. The planning method is also presented as a strong method for problem solving. The main concepts for implementing planners are discussed using examples.

Learning Objectives

  • Outline the model-based reasoning process.
  • Outline the case-based reasoning process.
  • Discuss hybrid systems.
  • Discuss the planning method and issues related to implementing planners.

Key Terms

model-based reasoning, case-based reasoning, cases similarity function, hybrid system, planning

Readings

Read the sections “Model-Based, Case Based and Hybrid Systems,” and “Planning” from Chapter 8, Strong Method Problem Solving.

Tasks

Practice the following exercises from Chapter 8 of the textbook:

  • Exercises 7, 10, and 13. You may want to use the Personal Workspace wiki on the course home page and/or share your observations with classmates in the COMP 456 General Discussion forum.

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