Important Questions of Artificial Intelligence
in this article, we have listed some of the major Important Questions of Artificial Intelligence.
Important Questions of Artificial Intelligence
Unit 1
1. “Can a machine think and behave like humans do”?
2. What is AI? Explain the approaches of AI.
3. Why AI is important in machine language?
4. Explain the foundation of AI in brief.
5. Discuss various definition of AI.
6. Explain the goals, application and techniques of AI.
7. What are the risks if we let machine to make a decision about human life?
8. What does a machine do better than a human in a war situation?
9. Should we limit the development of autonomous weapons?
Unit 2
1. For each of the following agents, develop a PEAS description of the task environment:
a. Robot soccer player;
b. Internet book-shopping agent,
c. Autonomous mars rover,
d. Mathematician’s theorem-proving assistant
2. Both the performance measure and the utility function measure how well an agent is doing. Explain the difference between the two.
3. Why environment agents play a vital role in AI? Explain vacuum cleaner agent with agent environment.
4. Define in your own words the following terms: agent, agent function, agent program, rationality, autonomy, reflex agent, model-based agent, goal-based agent, utility-based agent, learning agent.
5. What is agent? Explain different types of environment with example.
6. Define PEAS. Describe PEAS structure of interactive English tutor.
7. Explain types of agent environment? Draw the agent architecture.
8. What is intelligent agent? How does agents interact with environment?
Unit 3
1. Why searching is most important part of AI? Difference between uniformed and informed search with example.
2. What is searching? Describe different types of searching. Explain Algorithm of iterative of deepening search.
3. Compare depth first search and breath first search with example.
4. What is best-first search? Why is it considered as a heuristic search? Explain.
5. What is blind search? Describe the working principle of depth first search.
6. Why A* search algorithm is used for searching? Explain unformed search strategies.
7. What is panning? Differentiate between panning and searching.
8. Write Short note on: a) Uniform cost search b) Greedy search c) Heuristic function
d) Simulated annealing e) Genetic Algorithm f) A search
Unit 4
1. What do you understand by Min-Max search? Explain with example.
2. Explain alpha beta pruning test algorithm with example.
3. What is CSP? Sating necessary conditions and assumptions solve the following
crypto-athematic problem
a) SEND | b) CROSS | |||
+ MORE | + ROAD | |||
MONEY | DANGER | |||
4. Write short note on: a) Game Playing b) CSP problems c) Alpha beta pruning test
Unit 5
1. What is knowledge? Explain its types.
2. Explain knowledge and KBA? Using the truth table , prove P ß> Q are syntax and semantics.
3. What is predict logic? Differentiate with propositional logic.
4. What is a semantic net? Explain the significance of frame systems.
5. Explain semantic net and frames with examples.
6. Difference between propositional logic and FOFL.
7. Write short note on: a) Frames b) Semantic nets
Unit 6
1. What is learning? Explain inductive learning methods with example.
2. Explain learning by observation.
3. Explain techniques of explanation-based learning.
4. Why learning is important in AI? Explain the induction learning with suitable example.
5. What is rote learning? Describe Reinforcement learning with example.
6. Write short note: a) Rote learning b) Decisions trees
Unit 7
1. What is reasoning? Explain it types.
2. What is difference between monotonic and non-monotonic reasoning.
3. What are the methods of reasoning that deals with uncertainty? Explain.
5. What is the difference between uncertainty and case based reasoning.
6. Explain Bayesian network step in reasoning?
7. What is reasoning? How does Bayesian network deal with uncertainty? Explain.
Unit 8
1. What is an expert system? Discuss its advantages.
2. Draw a semantic diagram showing the various functional elements of an expert system. Explain the function of each of them.
3. What is knowledge acquisition? Explain knowledge elicitation techniques.
4. Explain the components of the knowledge base expert system. Also list the advantage of expert system.
5. Why expert system is important in AI? Explain components of expert system with diagram.
6. Difference between forward chaining and backward chaining with example.
7. Write short note on: a) Characteristics of Expert System b) Knowledge acquisition c) Design of expert system d) Application of ES
Unit 9
1. What is neural networks? Explain network architecture of artificial neural network.
2. Discuss major advantages of Artificial Neural Networks. Describe briefly back propagation training algorithm. Give different applications of neural networks.
3. What is learning? Difference between supervised and unsupervised learning with example.
4. Define machine learning. What are types? Explain any two learning methods.
5. How does back propagation work for learning in multilayer network.
6. Write short note on: a) Applications of neural networks b) Hopefield networks c) Learning methods d) Neural networks architectures
Unit 1o
1. Define natural language processing? Explain the components of NLU?
2. Discuss the history of NLP? Describe the steps in natural language processing.
3. What is parsing? Why NLP is necessary?
4. Write short note on: a) NLU b) Application of NLP c) Natural language vs computer language d) NLG
There has additionally been research done into making machines that can display feelings.artificial intelligence course