Inference Techniques, Bayesian Networks, and FOL in AI
Forward and Backward Chaining in AI
Inference engines in Artificial Intelligence use reasoning techniques to derive new information from existing facts. Two primary methods for this are Forward Chaining and Backward Chaining.
Forward Chaining (Data-Driven)
Forward Chaining is a data-driven inference technique used in Artificial Intelligence and Expert Systems. It starts with the known facts (initial data) and repeatedly applies inference rules to derive new facts until the desired goal is reached or no more rules can be applied.
It is called data-driven because the reasoning process begins with the available data and moves forward toward a conclusion.
Forward Chaining Algorithm
- Start with the known facts in the knowledge base.
- Find all rules whose
English with a size of 11.63 KB