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

The document discusses forward chaining and backward chaining in artificial intelligence. [1] Forward chaining starts with known facts and applies rules to infer new facts until reaching a goal. It is data-driven. [2] Backward chaining starts with the goal and works backwards to find supporting facts. It is goal-driven. [3] The key differences are that forward chaining is bottom-up while backward chaining is top-down, and forward chaining uses breadth-first search while backward chaining uses depth-first se

Author
Sanju Shree
Language
EN