This official 2024 final-term examination paper for Artificial Intelligence Theory (Course Code: CSAI-213-T) at the National University of Modern Languages (NUML) serves as an invaluable resource for BS Computer Science students in their fourth semester. Specially tailored to assess deep theoretical comprehension, the paper evaluates core domains such as state-space search formulations, heuristic search strategies (including A* and greedy best-first search), and game-playing algorithms like minimax with alpha-beta pruning. Additionally, it tests students on knowledge representation paradigms, first-order predicate logic, and the foundational concepts of machine learning and expert systems. By practicing with this past paper, students can master the essential mathematical and algorithmic frameworks necessary for constructing intelligent agents. Preparing with this resource helps learners identify recurring examination patterns, refine their analytical problem-solving skills under timed conditions, and bridge the gap between abstract AI concepts and practical system design. It is an indispensable tool for achieving academic excellence in mid-term and final-term assessments.
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BS Computer Science
The syllabus abstract for the CSAI-213-T final exam encompasses the essential theoretical foundations of modern artificial intelligence. It systematically evaluates students across key domains: problem-solving using uninformed and heuristic search methodologies, adversarial game playing, logical reasoning, and structured knowledge representation. The exam assesses both theoretical conceptualization and the mathematical formulation of intelligent systems, ensuring students understand how computational agents perceive, reason, and act. By balancing theoretical proofs with algorithmic step-by-step trace analysis, this exam structure prepares BS Computer Science undergraduates for advanced studies in machine learning, robotics, and cognitive computing.
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