Functions of an Inference Engine
- Rule Interpretation: The inference engine understands and applies rules, which are usually formatted as conditional statements like “if this, then that.” These rules guide how the engine processes information and makes decisions.
- Fact Handling: It takes in facts, which are pieces of information provided by the user or gathered from other sources. These facts are the raw data that the engine uses to apply the rules.
- Inference Making: Using the rules and facts, the inference engine deduces new information. This is the core function of the engine — to take known data and derive additional, unknown data or decisions from it.
- Resolution of Uncertainty: In many real-world scenarios, all necessary information may not be available, or the information can be ambiguous. The inference engine can handle such uncertainty, making reasoned guesses or decisions based on partial data.
- Explanation and Justification: After reaching conclusions, the inference engine can also provide explanations on how these conclusions were derived. This helps users understand the reasoning behind the decisions, increasing trust and transparency in the system.
What is an Inference Engine? Types and Functions
An inference engine is a component of an AI system that is responsible for drawing conclusions from a set of data. In other words, it is part of the AI system that makes deductions and predictions based on the information it has been given.