RTU Kota B.Tech 6th Semester Principles of Artificial Intelligence Question Paper 2024 (CSE/AI/IT)

RTU Principles of Artificial Intelligence 2024 Paper Review

The Principles of Artificial Intelligence course serves as the foundational pillar for understanding how machines simulate human cognitive processes. For Computer Science, AI, and IT students at Rajasthan Technical University, this subject is essential for mastering problem-solving paradigms, logical reasoning, and intelligent agent design. The 2024 examination emphasizes the transition from basic search techniques to sophisticated knowledge-based systems and uncertainty management.

Success in this exam requires a clear understanding of state-space search, formal logic, and the practical application of AI algorithms to real-world scenarios. This review outlines the exam structure and identifies the core modules essential for your preparation.

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. Expect questions on definitions such as the Turing test, rational agents, branching factor, heuristic functions, and the difference between monotonic and non-monotonic reasoning. Keep answers concise.
• Part B: Seven questions; answer five. Each is worth four marks. These are analytical. Prepare to compare BFS and DFS, explain the properties of the A* search algorithm, or discuss the advantages of semantic networks over production rules.
• Part C: Five major questions; answer three. Each is worth ten marks. These require deep explanations and traces. You may encounter problems requiring you to solve a constraint satisfaction problem, perform a resolution proof in first-order logic, or design a frame-based knowledge representation system.

Core Topics Evaluated in the Paper

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

Intelligent Agents and Search

Understand the environment types (e.g., fully observable, stochastic) and how they dictate agent design. Master search algorithms:

• Uninformed: BFS, DFS, Uniform Cost Search.
• Informed: Best-First Search and A* search. You must be able to prove the admissibility of a heuristic function.

Knowledge Representation and Logic

This module tests your ability to translate human language into formal mathematical structures. Study Propositional Logic and First-Order Logic (FOL). Be ready to convert English sentences into FOL expressions and perform resolution to prove a conclusion.

Reasoning and Planning

Focus on the logic behind decision-making. Understand how knowledge is structured using Semantic Networks, Frames, and Scripts. Study the basic components of a Planning system, such as STRIPS, and how they handle state transitions in goal-oriented environments.

Expert Systems and Uncertainty

Learn how AI systems handle incomplete or imprecise information. Understand Bayesian Networks, certainty factors, and fuzzy logic. For Expert Systems, study the architecture, including the inference engine, knowledge base, and user interface.

Answer Writing Strategy for High Marks

RTU evaluators look for logical progression and clear, structured technical content.

• Diagrams: AI is a visual subject. Always use a ruler to draw tree structures for search algorithms (BFS/DFS) or state-space diagrams. Clearly label your nodes, edges, and heuristic values.
• Formatting: Use a black pen for headings, logic formulas, and diagrams. Use a blue pen for your explanatory text.
• Logic Proofs: 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 "Supervised vs. Unsupervised learning" or "A* vs. IDA* search"—always present your answer in a table format.

Time Management During the Exam

• Part A (20 minutes): Finish these first. Aim for short, punchy definitions that hit the key technical keywords.
• Part B (40 minutes): Limit yourself to eight minutes per question. If a question involves a diagram, draw it first and then explain it.
• Part C (120 minutes): Devote 40 minutes to each of the three major questions. This is where you can secure your top marks. Use this time to write out full logic proofs and detailed algorithmic traces without rushing.