ai Unit 2 Most important 40 VVi MCQs Practise || INT - 428 || Problem Solving & Search in AI

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[00:00:03]I don't know what to grade upgrade on the certificate first semester revolution semester subject of grade of upgrade DVMs upload AI DVMs CPP DSA industry certificate revolution lucky section upload size lucky except except reject except first semester subject grade DVMs CGPA lucky CGPA upload first semester upload lucky improvement clear first semester winter lucky upload improvement clear lucky company internship CGPA upload direct upload lucky lucky lucky upload lucky lucky lucky upload lucky lucky lucky lucky upload lucky lucky certificate Oracle GMB lucky lucky upload subject lucky lucky lucky upload lucky upload lucky lucky lucky lucky lucky upload lucky problem upload lucky AI problem lucky lucky lucky upload lucky lucky first question In AI, a problem is typically defined by a set of random output, an initial state, and a goal state, a programming language, a fit a database. So, the right answer is an initial state and a goal state.

[00:02:13]Question number two, what is the purpose of state space search? To store data permanently, to explore possible state and find a path to the goal, to compress file, you have to create neural networks. So, the right answer is to explore possible states and find a path to the goal.

[00:02:31]Third, which of the following is an example of of a uninformed search algorithm? A star search, greedy best first search, breadth-first search, you have to hill climbing. So, the right answer is breadth-first search.

[00:02:47]Four, breadth-first search expand nodes depth-wise, randomly, level by level, you have to using heuristics. So, the right answer is level by level.

[00:02:58]Fifth, depth-first search uses queue, stack, heap, you have to hash table. So, the right answer is stack.

[00:03:06]Six, which search algorithm guarantees the shortest path when all edges cost are equal? DFS, BFS, hill climbing, you have to simulated annealing. So, the right answer is BFS.

[00:03:19]Seven, in state space search, a node represent a programming language, a state of the problem, you have to a database record, you have to a compiler.

[00:03:28]So, the right answer is a state of the problem.

[00:03:32]Eight, the branching factor refers to search depth, number of goal states, number of successor generated from a state, you have to last option number of heuristics used. So, the right answer is number of successors generated from a state.

[00:03:47]Nine, best-first search select nodes based on random choice, heuristic value, node color, so the right answer is heuristic value.

[00:03:58]10 A* search evaluates nodes using HN, GN, FN equal to GN plus HN or FN equal to GN minus HN. So right answer is FN equal to GN plus HN.

[00:04:15]11 In A* search, GN represent GN estimated cost to goal, actual cost from start node or goal node or heuristic value. So the right answer is actual cost from start node.

[00:04:30]12 In A* search, HN represent actual cost, heuristic estimate to goal, total cost or branching factor. So the right answer is heuristic estimate to goal.

[00:04:44]13 If GN equal to HN equal to FN FN GN plus HN the right answer is A option 10.

[00:04:54]14 In heuristic function, a heuristic function is a guaranteed solution, an estimate guiding search, a database query or a compiler instructions. So the right answer is an estimate guiding search.

[00:05:08]15 Which search algorithm is guaranteed optimal with an admissible heuristic? DFS, BFS, A* or hill climbing. So the right answer is A*.

[00:05:20]16 A heuristic is admissible if it overestimate cost, it never overestimates the true cost, it is always zero or it is negative. So the right answer is it never overestimates the true cost.

[00:05:37]17 Which search algorithm is also called greedy search? Best first search, DFS, BFS, uniform cost search. So the right answer is best first search.

[00:05:48]18. Constraint satisfaction problem involves variables and constraint, images and videos, compiler, or databases. So, the right answer is variable and constraints.

[00:05:59]19. Sudoku is an example of CSP, NLP, GAN, or CNN. So, the right Sudoku is an example of CSP. So, the right 20. Map coloring is a classical, sorry, classic example of reinforcement learning, CSP, clustering, or regression. So, the right answer is CSP.

[00:06:20]21. Which optimization technique uses gradient to update parameters? Breadth first search, gradient descent, DFS, or best first search. So, the right answer is gradient descent.

[00:06:33]22. The primary objective of optimization in in AI is increase memory usage, find the best solution among alternatives, reduce programming effort, or store more data. So, the right answer is find the best solution among alternatives.

[00:06:50]23. Gradient descent works by moving toward maximum error, randomly selecting solution, moving in the direction of steepest decrease in error, or last option exploring all possible state. So, the right answer is moving in the direction of steepest decrease in error.

[00:07:09]24. Which of the following is a metaheuristic algorithm? BFS, DFS, simulated annealing, or binary search.

[00:07:18]So, the right answer is simulated annealing.

[00:07:22]25. Simulated annealing is inspired by human learning, biological evolution, meta cooling processes, or neural networks. So, the right answer is meta cooling processes.

[00:07:34]26. Why does simulated annealing sometimes accept worse solution? To increase memory, to escape local optima, to reduce branching factor, you have it to guarantee shortest path. So, the right answer is to escape local optima.

[00:07:50]27, which of the following is another popular meta-heuristic? Genetic algorithm, BFS, DFS, uniform cost search. So, the correct answer is genetic algorithm.

[00:08:02]28, genetic algorithm are inspired by database system, natural evolution, operating system, you have a network link. So, the right answer is natural evolution.

[00:08:13]29, in AI problem design, complexity refers to number of colors used, difficulty and computational resource required, you have a programming language used, you have a file size. So, the right answer is difficulty and computational resources required.

[00:08:30]30, time complexity measures memory uses, execution time growth with input size, storage capacity, you have a network speed. So, the right answer is execution time growth with input size.

[00:08:43]31, space complexity refers to memory required by an algorithm, CPU speed, search depth, you have a heuristic value. So, the right answer is memory required by an algorithm.

[00:08:56]32, which factor is important while determining AI data requirement? Data quality, screen resolution, printer type, you have a keyboard layout. So, the right answer is data quality.

[00:09:08]33, insufficient training data generally leads to better accuracy, faster internet, poor model performance, you have an increased storage. So, the right answer is poor model performance.

[00:09:21]34, which of the following is a solution metric? Accuracy, keyboard size, monitor brightness, you have a processor brand.

[00:09:29]So, the right answer is accuracy.

[00:09:32]35, solution metrics are used to evaluate solution quality, increase RAM, design hardware, you have a key RAM, design hardware, create databases.

[00:09:43]So, the right answer is evaluate solution quality.

[00:09:47]36 reinforcement learning is mainly concerned with sequential decision-making, database management, data compression, or web development.

[00:09:57]So, the right answer is sequential decision-making.

[00:10:01]37 in re- enforcement learning an agent learns through rewards and penalties, compilers, databases, or file systems.

[00:10:11]So, the right answer is rewards and penalties.

[00:10:14]38 the entity that interact with the environment in re-enforcement learning is called agent, compiler, parser, server. So, the right answer is agent.

[00:10:26]39 which search algorithm is generally preferred when memory is limited? BFS, DFS, uniform cost search, A* So, the right answer is DFS.

[00:10:39]question if a state has five successor states, then its branching factor is 2, 3, 5, or 10. So, the right answer is 5.

[00:10:49]Okay. So, thank you and we'll meet you all in unit number three. Bye.