Artificial Intelligence Questions and Answers – Constraints Satisfaction Problems

«
»

This set of Basic Artificial Intelligence Questions and Answers focuses on “Constraints Satisfaction Problems”.

1. _________________ are mathematical problems defined as a set of objects whose state must satisfy a number of constraints or limitations.
a) Constraints Satisfaction Problems
b) Uninformed Search Problems
c) Local Search Problems
d) All of the mentioned
View Answer

Answer: a
Explanation: Refer definition of CSPs.

advertisement

2. Which of the Following problems can be modeled as CSP?
a) 8-Puzzle problem
b) 8-Queen problem
c) Map coloring problem
d) All of the mentioned
View Answer

Answer: d
Explanation: All of above problems involves constraints to be satisfied.

3. What among the following constitutes to the incremental formulation of CSP?
a) Path cost
b) Goal cost
c) Successor function
d) All of the mentioned
View Answer

Answer: d
Explanation: Initial state: The empty assignment ( ), in which all variables are unassigned.
Successor function: A value can be assigned to any unassigned variable, provided it does not conflict with previously assigned variables.
Goal test: The current assignment is complete.
Path cost: A constant cost (e.g., 1) for every step.
advertisement
advertisement

4. The term ___________ is used for a depth-first search that chooses values for one variable at a time and returns when a variable has no legal values left to assign.
a) Forward search
b) Backtrack search
c) Hill algorithm
d) Reverse-Down-Hill search
View Answer

Answer: b
Explanation: Refer definition of backtracking algorithm.

5. To overcome the need to backtrack in constraint satisfaction problem can be eliminated by ____________
a) Forward Searching
b) Constraint Propagation
c) Backtrack after a forward search
d) Omitting the constraints and focusing only on goals
View Answer

Answer: a
Explanation: Forward Searching is technique in which a forward check till k steps is made to analyze that the goal can be achieved satiating all constraints. With constraint propagation, constraints on a variable can be propagated to next level/hierarchy and satisfied at that level, eliminating need to backtrack.
advertisement

6. The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is called chronological-backtracking. It is also possible to go all the way to set of variable that caused failure.
a) True
b) False
View Answer

Answer: a
Explanation: Intelligent backtracking

7. Consider a problem of preparing a schedule for a class of student. What type of problem is this?
a) Search Problem
b) Backtrack Problem
c) CSP
d) Planning Problem
View Answer

Answer: c
Explanation: Schedule developer needs to consider all constraints on teacher as well as students.
advertisement

8. Constraint satisfaction problems on finite domains are typically solved using a form of ___________
a) Search Algorithms
b) Heuristic Search Algorithms
c) Greedy Search Algorithms
d) All of the mentioned
View Answer

Answer: d
Explanation: Any Search techniques can be used

9. Solving a constraint satisfaction problem on a finite domain is an/a ___________ problem with respect to the domain size.
a) P complete
b) NP complete
c) NP hard
d) Domain dependent
View Answer

Answer: b
Explanation: None.
advertisement

10. ____________ is/are useful when the original formulation of a problem is altered in some way, typically because the set of constraints to consider evolves because of the environment.
a) Static CSPs
b) Dynamic CSPs
c) Flexible CSPs
d) None of the mentioned
View Answer

Answer: b
Explanation: Refer to the definition of Dynamic CSPs algorithm.

11. Flexible CSPs relax on _______
a) Constraints
b) Current State
c) Initial State
d) Goal State
View Answer

Answer: a
Explanation: Definition of flexible CSPs.

12. Language/Languages used for programming Constraint Programming includes ____________
a) Prolog
b) C#
c) C
d) Fortrun
View Answer

Answer: a
Explanation: None.

13. Backtracking is based on ____________
a) Last in first out
b) First in first out
c) Recursion
d) Both Last in first out & Recursion
View Answer

Answer: d
Explanation: Recursion uses LIFO.

14. Constraint Propagation technique actually modifies the CSP problem.
a) True
b) False
View Answer

Answer: a
Explanation: Constraints are propagated towards goal node, modifying the actual problem.

15. When do we call the states are safely explored?
a) A goal state is unreachable from any state
b) A goal state is denied access
c) A goal state is reachable from every state
d) None of the mentioned
View Answer

Answer: c
Explanation: None.

16. Which of the following algorithm is generally used CSP search algorithm?
a) Breadth-first search algorithm
b) Depth-first search algorithm
c) Hill-climbing search algorithm
d) None of the mentioned
View Answer

Answer: b
Explanation: Provides backtrack facility.

Sanfoundry Global Education & Learning Series – Artificial Intelligence.

To practice basic questions and answers on all areas of Artificial Intelligence, here is complete set of 1000+ Multiple Choice Questions and Answers on Artificial Intelligence.

Participate in the Sanfoundry Certification contest to get free Certificate of Merit. Join our social networks below and stay updated with latest contests, videos, internships and jobs!

advertisement
advertisement
Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn | Youtube | Instagram | Facebook | Twitter