UNIT 2 - Inference in First-Order Logic: Forward and Backward Chaining ;ROLL NO -24111025

This presentation explains Inference in First-Order Logic, an important concept in Artificial Intelligence. It introduces inference and explains two major techniques: Forward Chaining and Backward Chaining. Forward Chaining is a data-driven approach that starts with known facts and derives new conclusions, whereas Backward Chaining is a goal-driven approach that starts with a goal and searches for facts to prove it. Simple examples are used to explain their working, differences, and applications in AI. *REFERENCES* 1. Russell, S. J., & Norvig, P. *Artificial Intelligence: A Modern Approach*, 4th Edition. Pearson, Chapter 9: Inference in First-Order Logic. 2. University of California, Berkeley. Introduction to Artificial Intelligence — Forward Chaining. CS 188. 3. University of California, Berkeley. Introduction to Artificial Intelligence — First-Order Logical Inference. CS 188. 4. Course notes and educational materials on First-Order Logic, Forward Chaining, and Backward Chaining.