Artificial Intelligence (AL-304) - Important Questions

Explain the scope and contribution of AI with real-life applications in human life and global challenges.

Discuss the need and motivation for AI in modern computing and technology.

Explain the A* search algorithm in detail, including how it combines other search strategies and why it is widely used.

Compare and contrast hill climbing and best-first search algorithms, including their strengths and weaknesses.

Explain how predicate logic / first-order logic is used for knowledge representation in AI.

Differentiate between monotonic and non-monotonic reasoning, with examples of scenarios where non-monotonic reasoning is essential in AI.

Explain the common problems and challenges in representing knowledge in AI systems.

Define Bayes' theorem and explain its significance and applications in probabilistic reasoning.

Differentiate between forward reasoning/chaining and backward reasoning/chaining.

Explain what semantic networks are in knowledge representation with an example.

Explain the minimax procedure for game playing, its objective, steps and working.

Explain the alpha-beta cutoff / pruning technique in game playing and its advantages.

What is the Block World problem in AI planning/robotics? Explain with an example and why it is significant.

Explain the components / architecture and capabilities / working of an expert system.

Explain how forward chaining and backward chaining / forward and backward reasoning are used in expert systems.

Design / develop a rule-based expert system for a domain such as disease diagnosis, legal advice or financial planning.