RTU Kota B.Tech 6th Semester Artificial Intelligence Question Paper 2022 (IT)

RTU Artificial Intelligence 2022 Paper Review

The Artificial Intelligence course for the IT branch at Rajasthan Technical University focuses on the fundamental algorithms and logical structures that enable machines to simulate human-like decision-making. The 2022 examination emphasized the transition from basic state-space search to sophisticated knowledge representation and expert systems. For IT students, this course is essential for understanding how to design intelligent agents, manage uncertainty, and structure complex knowledge bases.

This review breaks down the 2022 paper structure to help you understand the examiners' priorities and refine your preparation strategy for current assessments.

Understanding the Exam Pattern

The RTU theory examination is a three-hour paper worth 70 marks, organized into three parts:

• Part A: Ten compulsory questions, two marks each. Focus on definitions like "Heuristic Function," "Admissibility of A* Search," "Propositional Logic vs. First-Order Logic," "Expert System Components," and "Turing Test." Keep answers concise—strictly under 30 words.
• Part B: Seven questions; answer five. Each is worth four marks. These are analytical. Prepare to compare BFS and DFS, explain the state-space representation of a classic puzzle (like the 8-puzzle), describe the steps in a resolution proof, or outline the structure of a production system.
• Part C: Five major questions; answer three. Each is worth ten marks. These require detailed technical explanations or calculations. Expect problems on executing A* search, performing resolution in First-Order Logic, designing an Expert System, or solving Constraint Satisfaction Problems (CSP).

Core Topics Evaluated in the 2022 Paper

Focus your study time on these specific modules to maximize your score:

Search Strategies

This is the most critical module. You must be comfortable with both uninformed and informed search. Practice tracing BFS, DFS, and Uniform Cost Search. For informed search, master the A* algorithm—you should be able to manually calculate the $f(n) = g(n) + h(n)$ cost for every node and draw the final path.

Knowledge Representation and Logic

Understand how to translate human language into formal logic. Study the difference between Propositional Logic and First-Order Logic (FOL). Be prepared to convert English sentences into FOL expressions and perform resolution to prove a conclusion by contradiction.

Expert Systems and Uncertainty

Learn how AI systems handle incomplete or imprecise information. Study the architecture of an expert system, specifically the role of the inference engine, knowledge base, and user interface. For uncertainty, understand the use of Certainty Factors and Bayesian Networks at an introductory level.

Game Playing and Planning

Focus on the Minimax algorithm and Alpha-Beta pruning for games. You should be able to trace a game tree and determine the optimal move. For planning, understand the STRIPS approach and how AI systems decompose complex goals into actionable steps.

Answer Writing Strategy for High Marks

RTU evaluators prioritize logical rigor and visual clarity:

• Diagrams: AI is a visual subject. Always use a ruler to draw search trees, game trees, and state-space graphs. Clearly label your nodes, edges, and heuristic values. A clean, labeled diagram is essential for full marks.
• Formatting: Use a black pen for algorithm names, formulas, and diagrams. Use a blue pen for your explanatory text. Use bullet points for features, advantages, and limitations to make your answers scannable.
• Precision: When performing resolution in logic, show each step of the conversion to Clause Normal Form (CNF) before attempting the resolution. This demonstrates your process and ensures partial marks even if you make a calculation error.
• Comparative Tables: Whenever the paper asks to compare two concepts—like "BFS vs. DFS" or "Propositional vs. First-Order Logic"—always use a table to clearly delineate their differences.

Time Management During the Exam

• Part A (20 minutes): Finish these first to secure a solid foundation.
• Part B (40 minutes): Limit each answer to 8 minutes. Focus on drawing the required diagrams early so you have time to explain them.
• Part C (120 minutes): Devote 40 minutes per major question. Use this time to write out full logic proofs and detailed algorithmic traces. If a question asks for an algorithm, define it, state the steps, provide a small example or diagram, and mention a real-world use case.