SAMRAT ASHOK TECHNOLOGICAL INSTITUTE, VIDISHA, (M.P.)
(Engineering College)
Department of Electronics Engineering
Program- Electronics and Communication Engineering
Assignment - 2
Artificial Intelligence (EC-1881)
Submission Date: 20.03.2023
2
1.
Compare production based system with frame based system.
2.
What is the need for probability theory in uncertainty? Define conditional probability?
3.
What is the basic task of a probabilistic inference?
4.
What do you mean when you say knowledge representation?
5.
Explain the production based knowledge representation techniques?
6.
Explain the frame based knowledge representation?
7.
What are scripts? Explain in detail, with an example
8.
What is non-monotonic
onotonic reasoning? Explain the logics used for non
non-monotonic
monotonic reasoning.
9.
Explain non-monotonic reasoning and various logic associate with it.
10.
Write unification algorithm and explain resolution in predicate logic.
11.
Discuss the heuristic function. Explain how the heuristic function helps during search procedure. Explain
with a suitable example.
Define the heuristic search. Discuss benefits and short comings.
12.
13.
Discuss any four from the following heuristic search techniques. Explain the algorithm with the help of an
example.
(i). Hill Climbing: Steepest Ascent.
(ii).. Best First Search: The A Algorithms.
(iii).. Problem Reduction: The A
AO Algorithms.
(iv).. Constraints Satisfaction.
(v). Generate and Test.
14.
What is learning? What are types of learning? What is ROTE learning?
15.
Define Machine learning. What are the Fundamental concepts of machine learning?
16.
What are the types of machine learning?
17.
What is Adaptive learning? List the three core elements of Adaptive learning systems?
18.
Differentiate between Supervised learning and Unsupervised learning?
19.
What are Support Vector Machines?
20.
Differentiate search & planning and list out the various planning techniques.
21.
Explain about Hierarchical planning method with example?
22.
24.
What is expert system? What are the advantages of expert system? List out the limitations of expert
system?
What are the most important aspects and characteristics of expert systems? Also list the applications of
Expert Systems?
What is expert system shell? Sketch the Components of an Expert System Shell.
25.
Explain the probabilistic reasoning with suitable examples.
26.
Describe k-nearest neighbour learning Algorithm for continues valued target function.
27.
Discuss the major drawbacks of k-nearest neighbour learning algorithm and how it can be corrected.
28.
Explain the concept of Bayes theorem with an example.
29.
Explain Bayesian belief network and conditional independence with example.
30.
What are Bayesian belief networks? Where are they used?
31.
Explain Brute force MAP hypothesis learner? What is minimum description length principle.
32.
How is Naïve Bayesian classifier different from Bayesian classifier?
33.
Explain the confusion matrix with respect to Machine learning algorithms.
34.
Discuss the concept of Regression. Differentiate linear regression and logistic regression.
35.
What do you understand by deep learning? Discuss about the concept and application of convolution
neural network.
23.
(Dr. D. K. Shakya)
Assist. Prof. Dept.of Elex.