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Forward and Backward Chaining in AI

Forward and Backward Chaining are two important strategies in the field of AI. Its origin lies in the Expert System Domain of AI. Expert System was introduced to emulate the decision-making ability of human experts
Forward and Backward Chaining in AI

Forward chaining as the name suggests, start from the known facts and move forward by applying inference rules to extract more data, and it continues until it reaches to the goal, whereas backward chaining starts from the goal, move backward by using inference rules to determine the facts that satisfy the goal

Source- https://i0.wp.com/understandingcontext.com/wp-content/uploads/2012/11/Backward-Forward.png?resize=452%2C284

Forward chaining is used to get the goal from data hence it is called a data-driven inference technique while the Backward chaining is used to get the data from the goal it is called goal-driven inference techniques.

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Forward Chaining and backward chaining in AI - Javatpoint
Forward Chaining and backward chaining in AI with Tutorial, Introduction, History of Artificial Intelligence, AI, AI Overview, Application of AI, Types of AI, What is AI, etc.
Source- https://www.javatpoint.com/forward-chaining-and-backward-chaining-in-ai

#ForwardChaining #BackwardChaining #AI #ML #Probyto #ProbytoAI

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