a) What are the essential characteristics of production systems and how do they differ from other AI problem-solving approaches? (Unit 1)

b) What is the $A^{*}$ search algorithm, and how does it combine elements of other search algorithms? Why is it considered a popular choice for many AI applications? (Unit 1)

a) How can AI contribute to solving global challenges, such as climate change, healthcare or education? Provide specific examples. (Unit 1)

b) How does knowledge representation facilitate the process of deductive reasoning in AI? (Unit 2)

a) Compare and contrast propositional logic and predicate logic in terms of their expressiveness and applicability in different problem domains. (Unit 2)

b) Analyze a complex AI problem, such as natural language understanding and propose a knowledge representation scheme that would effectively address its challenges. (Unit 4)

a) Differentiate between scripts, schemas and frames. How are they applied in knowledge representation? (Unit 3)

b) Define Bayes' Theorem and explain its significance in probabilistic reasoning. (Unit 3)

a) Evaluate the limitations of frames in knowledge representation and propose enhancements or alternatives to address these limitations. (Unit 3)

b) What is the "block world" problem in robotics and why is it a significant challenge in the field of artificial intelligence? (Unit 4)

a) Given a simplified game tree for tic-tac-toe, apply the minimax procedure to determine the optimal move for a player at a particular state of the game. (Unit 4)

b) Evaluate the ethical implications of using NLP in surveillance and monitoring systems. How can these implications be addressed responsibly? (Unit 4)

a) List and describe the key characteristics that distinguish expert systems from other computer programs. (Unit 5)

b) Develop a comprehensive expert system for a complex domain, such as legal advice or financial planning. Explain how you would ensure the system's knowledge is up to date. (Unit 5)

Attempt any two:

a) Analyze the limitations of expert systems, including issues related to knowledge acquisition, knowledge representation. (Unit 5)

b) Differentiate between classical search algorithms and heuristic search algorithms (Unit 1)

c) Compare and contrast classical AI systems and modern AI systems in terms of their performance and adaptability. (Unit 1)

d) Define natural language processing (NLP) and its importance in AI. (Unit 4)