CE-803 (A) · Artificial Intelligence/Unsolved PYQ Paper
CE-803 (A) Artificial Intelligence - Dec 2024 Question Paper
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Unit 17 MarksaWhy is AI considered an interdisciplinary field, and how does it incorporate knowledge from multiple domains?
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Unit 17 MarksbCompare and contrast hill climbing and best-first search algorithms. What are their strengths and weaknesses?
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Unit 17 MarksaExplore the potential risks and limitations of heuristic search algorithms in AI. How can these risks be mitigated?
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Unit 27 MarksbList and explain some common problems and challenges in representing knowledge in AI systems.
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Unit 27 MarksaGive examples of scenarios where non-monotonic reasoning is essential in AI applications. What distinguishes it from monotonic reasoning?
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Unit 37 MarksbEvaluate the strengths and weaknesses of different inference methods (e.g., forward chaining, backward chaining) in AI and provide scenarios where each is more appropriate.
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Unit 37 MarksaWhat are semantic networks in the context of knowledge representation? Provide an example to illustrate their use.
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Unit 37 MarksbAnalyze a real-world problem and suggest how frames can be used to represent the knowledge required to solve it effectively?
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Unit 37 MarksaInvestigate the role of scripts, schemas and frames in AI chatbots and virtual assistants. Assess their potential for improving user interactions.
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Unit 47 MarksbExplain the minimax procedure in the context of game playing. What is its primary objective, and how does it work in games like chess?
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Unit 47 MarksaPropose a variation of the alpha-beta pruning algorithm that further optimize the search process in game trees and assess its potential advantages.
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Unit 47 MarksbInvestigate recent advancements in robotic systems for solving the block world problem. Discuss the innovations and technologies that have improved performance.
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Unit 57 MarksaDefine what Expert Systems (ES) are and explain their role in artificial intelligence and problem-solving.
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Unit 57 MarksbCompare and contrast the inference engines used in expert systems: forward chaining and backward chaining. Provide examples of scenarios where each is more suitable.
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Unit 5OR Choice7 MarksaBenefits of Expert Systems
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Unit 4OR Choice7 MarksbComponents of NLP
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Unit 3OR Choice7 MarkscCompare and contrast conceptual dependency analysis and semantic networks
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Unit 2OR Choice7 MarksdImportance of knowledge representation
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