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
B. The Certainty Factor (CF) is a numeric value that tells us about how likely an event or a statement is supposed to be true
Between 0 to 1 (Both inclusive)
Between 0 to 1 (Both exclusive)
Between -1 to +1
None of the above
Forward Chaining
Backward Chaining
Both a. and b.
None of the above
Probability
Inference
Heuristic Search
All of the above
Discrete or Continuous
Observable and partially-observable
Static and dynamic
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
Only valid data
Only invalid data
Both valid and invalid data
None of the above
Knowledge Level
Logical Level
Implementation Level
Can't be determined
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
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 i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above
Perceiving data from the environment
Adapting to the environment and situations
Acting upon the Environment
Reversing the previously performed actions
Dependent Events
Independent Events
Neither a. nor b.
Both a. and b.
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
0
-1
+1
Is decided in prior to every problem
Quantifiers are numbers ranging from 0-9.
Quantifiers are the quantity defining terms which are used with the predicates.
Quantifiers quantize the term between 0 and 1.
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
Thinking humanly
Adapting to the environment and situations
To rule over humans
Real Life Problem Solving
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
To solve real life problems
To play a game against a human in the same way as a human would do
To understand the environment variables
All of the above
Simple based Reflex agent
Model Based Reflex Agent
Goal Based Agent
All of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
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
Only i.
i. and iii.
ii. and iii.
iii. and iv.
100% accurate
Estimated values
Wrong values
None of the above
The Breadth First Search (BFS)
The Depth First Search (DFS)
The A* search
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
Constraints are a set of restrictions and regulations
While solving a CSP, the agent cannot violate any of the rules and regulations or disobey the restrictions mentioned as the constraints
It also focuses on reaching to the goal state
All of the above
Simple based reflex agent
Model based reflex agent
Goal based agent
Utility based agent