Constraints should be taken care of while solving the problem
The text is converted from readable format to non-readable format
If numbers are not sufficient, we can use special symbols like $#@% to encrypt the text
None of the above
C. If numbers are not sufficient, we can use special symbols like $#@% to encrypt the text
Partially observable environment
Dynamic nature of the environment
Inaccessible area in the environment
All of the above
i. v. ii. iv. iii.
i. ii. iii. iv. v.
ii. i. v. iv. iii.
None of the above
It provides solution in a reasonable time frame
It provides the reasonably accurate direction to a goal
It considers both actual costs that it took to reach the current state and approximate cost it would take to reach the goal from the current state
All of the above
Dependent Events
Independent Events
Neither a. nor b.
Both a. and b.
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Only valid data
Only invalid data
Both valid and invalid data
None of the above
Machine Learning
Deep Learning
Both (1) and (2)
None of the above
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Knowledge Level
Logical Level
Implementation Level
Can't be determined
3 levels
2 levels
4 levels
None of the above
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
100% accurate
Estimated values
Wrong values
None of the above
Dependent Events
Independent Events
Neither a. nor b.
Both a. and b.
3 types
2 types
User can define as many quantifiers he wants
None of the above
An agent which needs user inputs for solving any problem
An agent which can solve any problem on its own without any human intervention
An agent which needs an exemplary similar problem defined in its knowledge base prior to the actual problem
All of the above
2 types
3 types
4 types
None of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
100% accurate
Estimated values
Wrong values
None of the above
S=12; E=5; N=6; D=8; M=1; O=0; R=8; Y=2
S=9; E=5; N=6; D=7; M=1; O=0; R=8; Y=2
S=5; E=5; N=6; D=7; M=1; O=0; R=8; Y=2
S=9; E=5; N=9; D=7; M=1; O=0; R=8; Y=2
Between 0 to 1 (Both inclusive)
Between 0 to 1 (Both exclusive)
Between -1 to +1
None of the above
So that the agent can have decision making capability
So that the agent can think and act humanly
So that the agent can apply the logic for finding the solution to any particular problem
All of the above
N- Queens Problem
Chess
Sudoku
None of the above
Documentation for an AI agent
Production rules for an AI agent
Pseudo Code for an AI agent
None of the above
The certainty factor is same as the probability of any event
The Certainty Factor (CF) is a numeric value that tells us about how likely an event or a statement is supposed to be true
The Certainty Factor (CF) is a numeric value that tells us about how certain we are about performing a particular task
None of the above
To implement humanly behavior.
To deal with unknown environment.
To improve the reasoning capability of the agent.
All of the above
Uncertainty in Environment
Poor battery life of the system
Improper training time
All of the above
It is the way in which facts and information are stored in the storage system of the agent
When we conclude the facts and figures to reach a particular decision, that is called inference
We modify the knowledge and convert it into the format which is acceptable by the machine
All of the above.
In situations of uncertainty, probabilistic theory can help us give an estimate of how much an event is likely to occur or happen.
It helps to find the probability whether the agent should do the task or not.
It does not help at all.
None of the above.
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
Half true Half False
Somewhat true but not entirely false
Agent has no information about the event
Both a. and b.