a) Why is AI considered an interdisciplinary field, and how does it incorporate knowledge from multiple domains? (Unit 1)

b) Compare and contrast hill climbing and best-first search algorithms. What are their strengths and weaknesses? (Unit 1)

a) Explore the potential risks and limitations of heuristic search algorithms in AI. How can these risks be mitigated? (Unit 1)

b) List and explain some common problems and challenges in representing knowledge in AI systems. (Unit 2)

a) Give examples of scenarios where non-monotonic reasoning is essential in AI applications. What distinguishes it from monotonic reasoning? (Unit 2)

b) Evaluate the strengths and weaknesses of different inference methods (e.g., forward chaining, backward chaining) in AI and provide scenarios where each is more appropriate. (Unit 3)

a) What are semantic networks in the context of knowledge representation? Provide an example to illustrate their use. (Unit 3)

b) Analyze a real-world problem and suggest how frames can be used to represent the knowledge required to solve it effectively? (Unit 3)

a) Investigate the role of scripts, schemas and frames in AI chatbots and virtual assistants. Assess their potential for improving user interactions. (Unit 3)

b) Explain the minimax procedure in the context of game playing. What is its primary objective, and how does it work in games like chess? (Unit 4)

a) Propose a variation of the alpha-beta pruning algorithm that further optimize the search process in game trees and assess its potential advantages. (Unit 4)

b) Investigate recent advancements in robotic systems for solving the block world problem. Discuss the innovations and technologies that have improved performance. (Unit 4)

a) Define what Expert Systems (ES) are and explain their role in artificial intelligence and problem-solving? (Unit 5)

b) Compare and contrast the inference engines used in expert systems: forward chaining and backward chaining. Provide examples of scenarios where each is more suitable. (Unit 3)

Write short notes on any two of the following. (Unit 5)

a) Benefits of Expert Systems (Unit 5)

b) Components of NLP (Unit 4)

c) Compare and contrast conceptual dependency analysis and semantic networks (Unit 3)

d) Importance of knowledge representation (Unit 2)