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.
A. In situations of uncertainty, probabilistic theory can help us give an estimate of how much an event is likely to occur or happen.
Machine Learning
Deep Learning
Both (1) and (2)
None of the above
Knowledge Level
Logical Level
Implementation Level
Can't be determined
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Half true Half False
Somewhat true but not entirely false
Agent has no information about the event
Both a. and b.
Uncertainty in Environment
Poor battery life of the system
Improper training time
All of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
Partially observable environment
Dynamic nature of the environment
Inaccessible area in the environment
All of the above
Probability
Inference
Heuristic Search
All of the above
Searching for relevant data in the surroundings
Searching into its own knowledge base for solutions
Seeking for human inputs for approaching towards the solution
None of the above
0
-1
+1
Is decided in prior to every problem
Top-down approach
Bottom-up approach
No specific approach
According to precedence
Forward Chaining
Backward Chaining
Both a. and b.
None of the above
Estimation
Likelihood
Observations
All of the above
Movement and Humanly Actions
Perceiving and acting on the environment
Input and Output
None of the above
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
None of the above
Only valid data
Only invalid data
Both valid and invalid data
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
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
100% accurate
Estimated values
Wrong values
None of the above
100% accurate
Estimated values
Wrong values
None of the above
100% accurate
Estimated values
Wrong values
None of the above
Simple based Reflex agent
Model Based Reflex Agent
Goal Based Agent
All of the above
Discrete or Continuous
Observable and partially-observable
Static and dynamic
None of the above
Only valid data
Only invalid data
Both valid and invalid data
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
Only iv.
All i., ii., iii. and iv.
ii. and iv.
None of the above
Constraints should be taken care of while solving the problem
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None of the above