In the context of expert systems, explanation refers to the process of providing the user with a clear and understandable explanation of the reasoning process used by the system to arrive at a particular conclusion or recommendation. The aim of explanation is to enhance the user's understanding of the system's decision-making process and build trust in the system's recommendations.
Explanations in expert systems can be provided in various forms, such as textual descriptions, diagrams, and interactive dialogues. The type of explanation provided depends on the nature of the system and the user's requirements.
Explanation mechanisms can be categorized into two main types: justification-based and example-based. Justification-based explanation mechanisms provide a rationale for the system's conclusions by highlighting the evidence and rules used to arrive at the decision. Example-based explanation mechanisms provide the user with similar examples and cases to help them understand the system's reasoning process.
Effective explanations in expert systems should be clear, concise, and tailored to the user's level of expertise. They should also be transparent, understandable, and capable of being evaluated by the user.
