Only iv.
All i., ii., iii. and iv.
ii. and iv.
None of the above
A. Only iv.
i. v. ii. iv. iii.
i. ii. iii. iv. v.
ii. i. v. iv. iii.
None of the above
Thinking
Eating
Sleeping
None of the above
Encryption Problem
Constraint Satisfactory Problem
Number problem
All of the above
Sky and Land
Agent and environment
Yes or No
None of the above
For all
For each
For every
All of the above
Estimation
Likelihood
Observations
All of the above
2 types
3 types
4 types
None of the above
Between 0 to 1 (Both inclusive)
Between 0 to 1 (Both exclusive)
Between -1 to +1
None of the above
Knowledge Level
Logical Level
Implementation Level
Can't be determined
In propositional Logic, each sentence is a declarative sentence
In propositional logic, the sentence can have answers other than True or False
Propositional Logic is a type of knowledge representation in AI
None of the above
Uncertainty in Environment
Poor battery life of the system
Improper training time
All of the above
100% accurate
Estimated values
Wrong values
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
Responding and providing solution to the problem
Meeting the preference of the user
Meeting the goal
All of the above
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
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above
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
3 levels
2 levels
4 levels
None of the above
Restrictions
Rules
Regulations
All of the above
Thinking humanly
Adapting to the environment and situations
To rule over humans
Real Life Problem Solving
Simple based Reflex agent
Model Based Reflex Agent
Goal Based Agent
All of the above
0
-1
+1
Is decided in prior to every problem
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Modus Ponens
Resolution
Backward Chaining
All of the above
Dependent Events
Independent Events
Neither a. nor b.
Both a. and b.
Only valid data
Only invalid data
Both valid and invalid data
None 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 i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Knowledge Level
Logical Level
Implementation Level
Can't be determined