JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD B.Tech II Year ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Previous Question Paper (February - 2024 - R22)
Part-A is a compulsory question. Part-B consists of ten questions (numbered from 2 to 11) carrying 10 marks each. From each unit, there are two questions and the student should answer one of them. Hence, the student should answer five questions from Part-B.
Part A
How do you distinguish between narrow AI and general AI?
Answer
Narrow AI (or Weak AI) is designed to perform a specific task, such as facial recognition or language translation, within a limited context. General AI (or Strong AI) refers to a hypothetical system with the ability to understand, learn, and apply intelligence across any intellectual task that a human can perform.
What is state space representation, and how is it used in AI problem-solving?
Answer
State space representation is a mathematical model where a problem is defined by a set of states (configurations), an initial state, a goal state, and operators (actions) that transition the system between states. It is used in AI to map out all possible paths to a solution, allowing algorithms to search for the most efficient sequence of moves.
Discuss the advantages and limitations of generate and test.
Answer
Sign in to view the complete answer paper.
Define problem reduction in heuristic search.
Answer
Sign in to view the complete answer paper.
Define linear classifiers.
Answer
Sign in to view the complete answer paper.
Write the advantages and limitations of decision trees.
Answer
Sign in to view the complete answer paper.
What is case-based reasoning, and how does it work?
Answer
Sign in to view the complete answer paper.
What is ensemble learning, and how does it improve classification accuracy?
Answer
Sign in to view the complete answer paper.
Write the limitations of a single-layer perceptron.
Answer
Sign in to view the complete answer paper.
How does temporal difference learning relate to prediction and control in reinforcement learning?
Answer
Sign in to view the complete answer paper.
Part B
Briefly outline the historical development of AI from its inception today.
Answer
Sign in to view the complete answer paper.
What are the major branches of AI, and how do they differ? Explain.
Answer
Sign in to view the complete answer paper.
Discuss the importance of search algorithms in navigating state space.
Answer
Sign in to view the complete answer paper.
Discuss the ethical considerations associated with AI applications in autonomous vehicles.
Answer
Sign in to view the complete answer paper.
Describe how hill climbing works and its application in problem-solving.
Answer
Sign in to view the complete answer paper.
Discuss the importance of effective knowledge management in AI applications.
Answer
Sign in to view the complete answer paper.
Discuss the differences between the best-first search and the A* algorithm with a suitable example.
Answer
Sign in to view the complete answer paper.
Explain the optimality conditions of A*.
Answer
Sign in to view the complete answer paper.
Describe the key components of a machine learning system.
Answer
Sign in to view the complete answer paper.
Define Bayesian networks and their use in probabilistic modeling. How do Bayesian networks represent and update probabilities? Explain.
Answer
Sign in to view the complete answer paper.
How are decision trees constructed, and what criteria are used for splitting nodes? Explain.
Answer
Sign in to view the complete answer paper.
How does an intelligent agent perceive its environment and take action? Explain.
Answer
Sign in to view the complete answer paper.
What role do kernel functions play in SVM? Explain the concept of the kernel trick in SVM.
Answer
Sign in to view the complete answer paper.
How does a k-nearest neighbor differ from other classification methods? Explain.
Answer
Sign in to view the complete answer paper.
Explain the concept of fuzzy sets and membership functions.
Answer
Sign in to view the complete answer paper.
Differentiate between bagging and boosting techniques in ensemble learning.
Answer
Sign in to view the complete answer paper.
Explain the concepts of neurons, weights, and activation functions in an ANN.
Answer
Sign in to view the complete answer paper.
Discuss the exploration-exploitation trade-off in Q-learning.
Answer
Sign in to view the complete answer paper.
Explain the Q-learning algorithm in the context of reinforcement learning.
Answer
Sign in to view the complete answer paper.
Define the Markov decision problem and its components. How does the Markov property influence decision-making in MDPs? Explain.
Answer
Sign in to view the complete answer paper.