Artificial Intelligence MCQ
Our website provides a wide range of Artificial Intelligence MCQs to help learners test and strengthen their knowledge of AI concepts. The questions cover topics like machine learning, neural networks, natural language processing, expert systems, robotics, and AI applications. Each MCQ includes explanations to make learning easier and more effective. This platform is designed for students, professionals, and exam aspirants, making AI preparation simple, engaging, and useful for both academic growth and career success.
Q1. Which of the following is an example of a weak AI system?
A. Self-driving car
B. Chess-playing program
C. Human-level robot
D. General problem solver
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Q2. In AI, which search strategy explores all nodes at the present depth before moving to the next?
A. Depth First Search
B. Breadth First Search
C. Hill Climbing
D. A* Search
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Q3. Which AI technique involves learning from labeled training data?
A. Unsupervised learning
B. Supervised learning
C. Reinforcement learning
D. Evolutionary learning
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Q4. Which of the following is a knowledge representation technique in AI?
A. Decision trees
B. Neural networks
C. Frames and semantic networks
D. Backpropagation
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Q5. What does NLP in Artificial Intelligence stand for?
A. Natural Logic Processing
B. Neural Language Prediction
C. Natural Language Processing
D. Network Language Parsing
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Q6. Which algorithm is widely used in training neural networks?
A. Decision tree
B. Backpropagation
C. Breadth-first search
D. K-means
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Q7. The Turing Test is used to measure:
A. System performance
B. Human intelligence
C. Machine intelligence
D. Algorithm efficiency
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Q8. Which type of learning is used in game-playing AI agents like AlphaGo?
A. Supervised learning
B. Unsupervised learning
C. Reinforcement learning
D. Semi-supervised learning
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Q9. Which AI search algorithm guarantees finding the optimal solution using heuristics?
A. Depth First Search
B. Hill Climbing
C. A* Search
D. Greedy Search
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Q10. Which neural network model is widely used for image recognition?
A. Recurrent Neural Network (RNN)
B. Convolutional Neural Network (CNN)
C. Perceptron
D. Hopfield Network
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Q11. In AI, knowledge base in expert systems contains:
A. Facts and rules
B. Only facts
C. Only rules
D. Training data
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Q12. Which of the following is an application of computer vision in AI?
A. Speech recognition
B. Face detection
C. Machine translation
D. Chatbots
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Q13. Which learning algorithm is used in clustering?
A. Supervised learning
B. Reinforcement learning
C. Unsupervised learning
D. Deep learning
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Q14. Which of the following is a limitation of AI?
A. Automation of tasks
B. Bias in decision-making
C. Data-driven models
D. High accuracy
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Q15. Which approach in AI uses inspiration from biological neurons?
A. Genetic algorithms
B. Rule-based systems
C. Neural networks
D. Decision trees
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Q16. Which algorithm is commonly used for shortest path in AI navigation?
A. Greedy search
B. Dijkstra’s algorithm
C. A* algorithm
D. Bellman-Ford algorithm
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Q17. Which field of AI is concerned with reasoning under uncertainty?
A. Fuzzy logic
B. Neural networks
C. Supervised learning
D. Backpropagation
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Q18. Which of the following is a real-world application of reinforcement learning?
A. Spam filtering
B. Autonomous driving
C. Face recognition
D. Language translation
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Q19. Which algorithm is used for decision-making in game AI (e.g., chess)?
A. Perceptron
B. Minimax
C. Backpropagation
D. K-means
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Q20. Which of the following is an unsupervised learning algorithm?
A. Decision Tree
B. K-means clustering
C. Naive Bayes
D. Linear Regression
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