The following quiz “Artificial Intelligence (AI) MCQ Questions and Answers” provides Multiple Choice Questions (MCQs) related to Artificial Intelligence (AI). These Artificial Intelligence (AI) MCQs are also Interviews (campus interview, walk-in interview, company interview), Placement or recruitment, entrance examinations, and competitive examinations oriented. You can practice the below questions to improve your Artificial Intelligence (AI) skills. You can click on the View Answer button to check the answer if you needed. Let’s solve this Artificial Intelligence MCQ Questions and Answers Quiz.

📚 Table of Contents:

• Pages 1–3 (Q1–Q30): Turing Test, AI vs ML vs DL, neural networks basics, NLP intro, computer vision intro, reinforcement learning basics, A* algorithm, expert systems, search algorithms (BFS/DFS), heuristics, minimax, alpha-beta pruning, knowledge representation, fuzzy logic, genetic algorithms, Bayesian networks
• Page 4 (Q31–Q40): Problem-solving agents, state space search, uninformed vs informed search, greedy best-first search, hill climbing, simulated annealing, constraint satisfaction problems (CSP), arc consistency, backtracking, game theory in AI
• Page 5 (Q41–Q50): Knowledge representation (propositional/first-order logic), inference rules (modus ponens, resolution), forward chaining, backward chaining, Prolog basics, ontologies, semantic networks, frames, description logic, probabilistic reasoning
• Page 6 (Q51–Q60): Planning (STRIPS, PDDL), plan space search, partial-order planning, conditional planning, temporal planning, multi-agent systems, agent architectures (reactive/deliberative/hybrid), belief-desire-intention (BDI), game theory (Nash equilibrium), mechanism design
• Page 7 (Q61–Q70): Markov Decision Processes, Q-learning, policy gradient methods, model-based vs model-free RL, exploration vs exploitation, reward shaping, inverse RL, multi-arm bandit problem, deep RL (DQN, PPO, A3C), applications of RL
• Page 8 (Q71–Q80): NLP fundamentals (tokenization, parsing, POS tagging, NER), language models (n-gram, neural), machine translation, question answering, summarization, dialogue systems, chatbots, information retrieval, knowledge graphs in NLP
• Page 9 (Q81–Q90): Computer vision fundamentals, image processing, feature detection (SIFT/SURF/HOG), object recognition, scene understanding, optical flow, 3D reconstruction, medical image AI, autonomous driving perception, visual question answering
• Page 10 (Q91–Q100): AI ethics (bias, fairness, accountability), explainable AI, AI safety, AGI debate, AI regulation, large language models impact, AI in healthcare/education/science, future of AI, current research frontiers

You can practice these Artificial Intelligence MCQ here and if you want a pdf of this artificial intelligence (AI) MCQ Questions and Answers, we will provide a downloading link here soon so please keep visiting here for further modifications.

01. Artificial Intelligence is all about_____

1. Making a machine Intelligent
2. Programming on Machine with your Own Intelligence
3. Putting your intelligence in Machine
4. Playing a game on the Computer

02. The application/applications of Artificial Intelligence is/are

1. Expert Systems
2. Gaming
3. Vision Systems
4. All of the above

03. Strong Artificial Intelligence (AI) is

1. The embodiment of human intellectual capabilities within a computer
2. A set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans
3. The study of mental faculties through the use of mental models implemented on a computer
4. All of the mentioned

04. Who is known as the father of Artificial Intelligence?

1. Doug Cutting
2. John McCarthy
3. William S
4. Rasmus Lerdorf

05. LISP was created by?

1. Marvin Minsky
2. Allen Newell and Herbert Simon
3. John McCarthy
4. Alan Turing

06. Which search method takes less memory?

1. Breadth-First search
2. Optimal search
3. Linear Search
4. Depth-First Search

07. Weak AI is

1. A set of computer programs that produce output that would be considered to reflect intelligence if it were generated by humans
2. The study of mental faculties through the use of mental models implemented on a computer
3. The embodiment of human intellectual capabilities within a computer
4. All of the above

08. Expert Ease was developed under the direction of __________

1. John McCarthy
2. Lofti Zadeh
3. Donald Michie
4. Alan Turing

09. If a robot can alter its own trajectory in response to external conditions, it is considered to be

1. mobile
2. intelligent
3. open loop
4. non-servo

10. An AI system developed by Daniel Bobrow to read and solve algebra word problems

1. STUDENT
2. SIMD
3. BACON
4. SHRDLU