32. Forward Chaining and Backward Chaining in AI | Artificial Intelligence | CSE

This lecture is a part of a lecture series given by Ms Ishika on Artificial intelligence for Computer Science Engineering students at Binary Institute.
Description
Forward Chaining and Backward Chaining are important inference techniques in Artificial Intelligence used for reasoning and decision-making in knowledge-based systems. In this video, we explore how these two approaches work and how they differ in solving problems.

You will learn that Forward Chaining is a data-driven approach that starts with known facts and applies rules to derive new information, while Backward Chaining is a goal-driven approach that starts with a goal and works backward to find supporting facts. We also discuss their applications, advantages, and when to use each method.

This topic is especially important for Computer Science Engineering (CSE) students, as it provides a strong foundation in logical reasoning, expert systems, and AI-based problem-solving techniques.

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Видео 32. Forward Chaining and Backward Chaining in AI | Artificial Intelligence | CSE канала Binary