B.E/B.TECH DEGREE EXAMINATION, MAY/JUNE 2009
Sixth semester
3rd year.
(Regulation 2004)
department of Computer science and engineering
CS 1351 – ARTIFICIAL INTELLIGENCE
(Common to B.E (part –time) fifth semester regulation 2005)
PART A- (10 x 2 = 20 marks)
1. Define ideal rational agent
2. Define a data type to represent problems and nodes.
3. How does one characterize the quality of heuristic?
4. Formally define game as a kind of search problems.
5. Joe, tom and Sam are brothers-represent using first order logic symbols.
6. List the canonical forms of resolution.
7. What is Q-learning?
8. List the issues that affect the design of a learning element.
9. Give the semantic representation of “john loves Mary”.
10. Define DCG.
PART B – (5 x 16 = 80 marks)
11. (a) explain uninformed search strategies.(16)
(Or)
(b) How searching is used to provide solutions and also describe some real world problems? (16)
12. (a) describe alpha-beta pruning and its effectiveness.(16)
(Or)
(b) Write in detail about any two informed search strategies. (16)
13. (a) elaborate forward and backward chaining.(16)
(Or)
(b) Discuss the general purpose ontology with the following elements:
(i) Categories (4)
(ii) Measures (4)
(iii) Composite objects (4)
(iv) Mental events and mental objects.(4)
14. (a) explain with an example learning in decision trees.(16)
(Or)
(b) Describe multilayer feed-forward networks. (16)
15.(a) (i) list the component steps of communication.(8)
(ii) Write short notes about ambiguity and disambiguation.(8)
(Or)
(b) Discuss in detail the syntactic analysis (PARSING). (16)
Sixth semester
3rd year.
(Regulation 2004)
department of Computer science and engineering
CS 1351 – ARTIFICIAL INTELLIGENCE
(Common to B.E (part –time) fifth semester regulation 2005)
PART A- (10 x 2 = 20 marks)
1. Define ideal rational agent
2. Define a data type to represent problems and nodes.
3. How does one characterize the quality of heuristic?
4. Formally define game as a kind of search problems.
5. Joe, tom and Sam are brothers-represent using first order logic symbols.
6. List the canonical forms of resolution.
7. What is Q-learning?
8. List the issues that affect the design of a learning element.
9. Give the semantic representation of “john loves Mary”.
10. Define DCG.
PART B – (5 x 16 = 80 marks)
11. (a) explain uninformed search strategies.(16)
(Or)
(b) How searching is used to provide solutions and also describe some real world problems? (16)
12. (a) describe alpha-beta pruning and its effectiveness.(16)
(Or)
(b) Write in detail about any two informed search strategies. (16)
13. (a) elaborate forward and backward chaining.(16)
(Or)
(b) Discuss the general purpose ontology with the following elements:
(i) Categories (4)
(ii) Measures (4)
(iii) Composite objects (4)
(iv) Mental events and mental objects.(4)
14. (a) explain with an example learning in decision trees.(16)
(Or)
(b) Describe multilayer feed-forward networks. (16)
15.(a) (i) list the component steps of communication.(8)
(ii) Write short notes about ambiguity and disambiguation.(8)
(Or)
(b) Discuss in detail the syntactic analysis (PARSING). (16)
