Fuzzy Logic (FL) is a method by which any expert system or any agent based on Artificial Intelligence performs reasoning under uncertain conditions.
In this method, the reasoning is done in almost the same way as it is done in humans.
In this method, all the possibilities between 0 and 1 are drawn.
All of the above
D. All 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
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
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
For all
For each
For every
All 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
Knowledge Level
Logical Level
Implementation Level
Can't be determined
Only valid data
Only invalid data
Both valid and invalid data
None of the above
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Forward Chaining
Backward Chaining
Both a. and b.
None of the above
Probability
Inference
Heuristic Search
All of the above
Machine Learning
Deep Learning
Both (1) and (2)
None of the above
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above
Partially observable environment
Dynamic nature of the environment
Inaccessible area in the environment
All of the above
When the agent moves from one place to another, then it is called the move of the agent
When the agent goes from one state to another, it is known as a move
Both (1) and (2)
None of the above
Between 0 to 1 (Both inclusive)
Between 0 to 1 (Both exclusive)
Between -1 to +1
None of the above
Sky and Land
Agent and environment
Yes or No
None of the above
Uncertainty arises when we are not 100 percent confident in our decisions
Whenever uncertainty arises, there is needs to be an estimation taken for getting to any conclusion
The AI agent should take certain decisions even in the situations of uncertainty
All of the above
100% accurate
Estimated values
Wrong values
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
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
Left sided and right sided
i. v. ii. iv. iii.
i. ii. iii. iv. v.
ii. i. v. iv. iii.
None of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
None of the above
i. and ii.
i., ii. and iii.
ii. and iii.
iii. and iv.
In deductive logic, the complete evidence is provided about the truth of the conclusion made
A top-down approach is followed
The agent uses specific and accurate premises that lead to a specific conclusion
All of the above
N- Queens Problem
Chess
Sudoku
None of the above
100% accurate
Estimated values
Wrong values
None of the above
Knowledge Level
Logical Level
Implementation Level
Can't be determined
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.
0
-1
+1
Is decided in prior to every problem
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above