Unit 2-16 mark

 

1)       (i) Write short notes on syntax & semantics of propositional logic (8)
       (ii)   Explain Conjunctive normal form with example (8)

2)      (i) Define the syntactic elements of first-Order logic  (8)
      (ii)  Illustrate the use of first-order logic to represent knowledge. (8)                                                   

      3)      Explain the steps involved in the knowledge Engineering process. Give an example.  (16)

4)      Explain with an example

(a)    forward chaining                                                (8)

                                 (b)  Backward chaining                                            (8)
      5) (i)  Explain the unification  with an example.(8)
           (ii) Explain Resolution for first order logic with example. (8)

Unit 2-2 mark

Unit II

2 Mark questions

1. What is propositional logic?
2. What are the elements of propositional logic?
3. What is inference? 
4. Define Modus Ponen’s rule in Propositional logic
5. What is entailment?
6. What are knowledge based agents?
7. What is Knowledge Base?
8. Explain in detail the connectives used in propositional logic.
9. Define First order Logic? 
10.  Specify the syntax of  First-order logic in BNF form.
11. What are the syntactic elements of First Order Logic?
12. What the types of quantifiers?
13. Explain Universal Quantifiers with an example
14. Explain Existential quantifiers with an example.
15. What are nested quantifiers?
16. Explain the connection between Universal Quantifiers   and  Existential quantifiers
17. What are the steps associated with  the knowledge Engineering process?
18. Give examples on usage of First Order Logic.
19. What is universal instantiation?
20. What is forward chaining? Explain with an example.
21. What is backward chaining ? Explain with an example.
22. What are semantic networks? 
23. Define generalized Modus Ponen’s rule in First order Logic.   
24. Define a Sentence?
25. What are the components of Propositional Logic(syntax & Semantics)? 
26. What is Horn Clause?
27. Differentiate between prepositional versus first-order logic
28. What is unification algorithm?
29. How can you represent the resolution in predicate logic?  
    
    

   

artificial class notes.

ai class notes





To see the class notes for Unit I and Unit II  click on the above link "ai class notes".

Unit 1

PART B

1) a. Elaborate the approaches for AI with eg. (8)
    b. How is a task environment specified? (8)
2) What are the task environment natures? (16)
3) a. Describe the various properties of the task environment. (8)
    b. Write PEAS description for at least four agent types. (8)
4) a. Write the environment characteristics of any four agent type. (8)
    b. Explain in detail Simple reflex agent. (8)
5) Explain in detail any of the four agent structure. (16)
6) a. Explain in detail Model based reflex agent. (8)
     b. Explain in detail Goal based reflex agent. (8)
7) a. Explain in detail Utility based reflex agent. (8)
     b. Explain in detail learning agent. (8)
8) Explain in detail Problem solving agent. (16)
9) a. Distinguish an agent of AI and non AI program. (8)
    b. Explain tree search algorithm in detail. (8)
10) Give an example and explain the toy and real world problem. (16)
11) Explain how solutions are searched by a problem solving agent. (16)
12) a. Write short notes on the following Depth First Search, breadth first search,uniform cost search, 
       backtracking search. (8)
      b. Write short notes on Iterative deepening depth first search. (8)
13) a. Write short notes on Depth limited search. (8)
      b. State how repeated states are avoided and give an algorithm. (8)
14) Explain any two heuristic searches in detail. (16)
15) a. Explain Hill climbing in detail. (8)
       b. Explain A* search in detail. (8)
16) a. Explain simulated annealing search in detail. (8)
      b. Explain Memory bounded heuristic search in detail. (8)
17) Explain any two local search algorithms in detail. (16)
18) a. Explain genetic algorithm as a local search. (8)
      b. Explain online search agent working using depth first exploration. (8)
19) a. Write in detail the learning of an agent in online search method. (8)
      b. Explain constraint satisfaction problem with an example. (8)

Unit: 1

2 mark

1) What are the approaches followed to have AI?
2) Define AI.
3) Define Agent with a diagram.
4) What is a rational agent?
5) What are the elements of an agent?
6) State the factors that make up rationality.
7) Distinguish omniscience and rationality.
8) What is a task environment?
9) What is a PEAS description?
10) Write a PEAS description for an automated taxi?
11) Write a PEAS description for a vacuum cleaner?
12) Write a PEAS description for a wumpus world?
13) What is agent program and agent architecture?
14) What is a software agent?
15) State the difference between utility function and performance measure?
16) State the difference between agent function and agent program?
17) Give the steps adopted by a problem solving agent.
18) What is a fringe?
19) How is problem solving algorithm performance measured?
20) What are the components that a node represents in a search tree?
21) What is informed search?
22) What is local search?
23) What are the various types of informed search?
24) When A* is optimal?
25) What is admissible heuristic?
26) What is greedy best first search?
27) What is A* search?
28) What is SMA* search?
29) What are the types of memory bounded heuristic search?
30) What are the factors that affect the quality of a heuristic?
31) What is a local search algorithm?
32) What are the various local search algorithm?
33) What are the problems faced by a local search algorithm?
34) What are the components of a genetic algorithm?
35) What is online search and offline search?