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ai Unit 2 Most important 40 VVi MCQs Practise || INT - 428 || Problem Solving & Search in AI
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231 views17likes10:54JustLPUThings2.0Original Release: 2026-05-31

This video covers essential AI search concepts including problem formulation (initial state, goal state, and state space), uninformed search algorithms (BFS expands level-by-level using queues, DFS uses stacks), informed search (A* uses FN = GN + HN where GN is actual cost and HN is heuristic estimate), admissible heuristics that never overestimate true cost, constraint satisfaction problems (CSP) like Sudoku and map coloring, optimization techniques (gradient descent for steepest error decrease, simulated annealing for escaping local optima), and reinforcement learning fundamentals (agents learning through rewards and penalties for sequential decision-making).

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