ARTIFICIAL INTELLIGENCE 2018 MCA 4th Sem AKTU
Printed Pages: 1 Sub Code: RCA403
Paper Id: 214431 Roll No. _____________________
MCA
(SEM IV) THEORY EXAMINATION 2017-18
ARTIFICIAL INTELLIGENCE
Time: 3 Hours Total Marks: 70
Note: Attempt all Sections. If require any missing data; then choose suitably.
SECTION A
1. Attempt all questions in brief. 2 x 7 = 14
- What is meant by the term artificial intelligence? How it is different from natural intelligence?
- Discuss branch and bound search algorithms.
- Differentiate between local search and global search.
- Transform the following formula to Prenex normal form:
- Define forward chaining and backward chaining with example.
- Explain in brief the concept of reinforcement learning.
- Write a short note on support vector machines.
SECTION B
2. Attempt any three of the following: 7 x 3 = 21
- What is an intelligent agent? Discuss any two types of intelligent agents.
- Explain steepest-ascent hill climbing algorithm. What are the problems with hill climbing algorithm?
- Describe Hidden Markov Model with suitable example. Also discuss its role in probabilistic reasoning.
- Discuss Maximum-likelihood parameter learning for complete data with discrete models.
- What do you mean by classification? Discuss the process of classification with the help of a diagram.
SECTION C
3. Attempt any one part of the following: 7 x 1 = 7
- Discuss the historical development of artificial intelligence.
- For each of the following agents, develop a PEAS description of the task environment:
- Mathematician’s theorem proving assistant
- Satellite image analysis system
- Internet book shopping agent
- Medical diagnosis system
4. Attempt any one part of the following: 7 x 1 = 7
- Discuss simulated annealing search algorithm with its advantages and disadvantages.
- What are the steps to define a problem? Explain. Also discuss various components of a problem.
5. Attempt any one part of the following: 7 x 1 = 7
- Discuss algorithm of conversion to clause form Convert the following to clause form using algorithm:
![\forall x \left[ Brick \left(x\right) \longrightarrow \left(\exists y \left[ On \left( x, y\right) \cap \neg Pyramid \left(y\right)\right] \cap \neg \exists y \left[ On \left( x, y\right) \cap On \left(y, x\right)\right] \cap \forall y \left[ \neg Brick \left(y\right) \longrightarrow \neg Equal \left( x, y\right)\right]\right)\right]](data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSI4MTciIGhlaWdodD0iMTciIHZpZXdCb3g9IjAgMCA4MTcgMTciPjxyZWN0IHdpZHRoPSIxMDAlIiBoZWlnaHQ9IjEwMCUiIHN0eWxlPSJmaWxsOiNjZmQ0ZGI7ZmlsbC1vcGFjaXR5OiAwLjE7Ii8+PC9zdmc+)
- Explain the concept of Alpha beta pruning. Write alpha beta search algorithm.
![\forall x \left[ Brick \left(x\right) \longrightarrow \left(\exists y \left[ On \left( x, y\right) \cap \neg Pyramid \left(y\right)\right] \cap \neg \exists y \left[ On \left( x, y\right) \cap On \left(y, x\right)\right] \cap \forall y \left[ \neg Brick \left(y\right) \longrightarrow \neg Equal \left( x, y\right)\right]\right)\right]](https://s0.wp.com/latex.php?latex=%5Cforall+x+%5Cleft%5B+Brick+%5Cleft%28x%5Cright%29+%5Clongrightarrow+%5Cleft%28%5Cexists+y+%5Cleft%5B+On+%5Cleft%28+x%2C+y%5Cright%29+%5Ccap+%5Cneg+Pyramid+%5Cleft%28y%5Cright%29%5Cright%5D+%5Ccap+%5Cneg+%5Cexists+y+%5Cleft%5B+On+%5Cleft%28+x%2C+y%5Cright%29+%5Ccap+On+%5Cleft%28y%2C+x%5Cright%29%5Cright%5D+%5Ccap+%5Cforall+y+%5Cleft%5B+%5Cneg+Brick+%5Cleft%28y%5Cright%29+%5Clongrightarrow+%5Cneg+Equal+%5Cleft%28+x%2C+y%5Cright%29%5Cright%5D%5Cright%29%5Cright%5D&bg=ffffff&fg=000&s=0&c=20201002)
6. Attempt any one part of the following: 7 x 1 = 7
- Discuss various application domains of machine learning.
- Describe major step involved in a learning process. Also discuss how learning systems are classified.
7. Attempt any one part of the following: 7 x 1 = 7
- What is pattern recognition? Explain various steps involved in the designing of a pattern recognition system with the help of a diagram.
- Explain nearest neighbor rule used for classification.
Thank You!
