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Forward vs Backward Chaining in AI by Goku Kumar is a document available to read on EtoBox.

What is Forward vs Backward Chaining in AI about?

Forward chaining is a method of reasoning that applies inference rules to existing data to derive new conclusions until reaching a goal. It starts with known facts and works forward to draw conclusions, following a bottom-up approach. In forward chaining, rules are used to deduce new facts from existing facts and rules in a data-driven manner until a goal is reached.

Author

Goku Kumar

Language

EN