i. and ii.
i., ii. and iii.
ii. and iii.
iii. and iv.
B. i., ii. and iii.
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
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
Conditional Probability gives 100% accurate results.
Conditional Probability can be applied to a single event.
Conditional Probability has no effect or relevance or independent events.
None of the above.
Knowledge Level
Logical Level
Implementation Level
Can't be determined
Perceiving data from the environment
Adapting to the environment and situations
Acting upon the Environment
Reversing the previously performed actions
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
Left sided and right sided
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
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
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
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
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
Simple based Reflex agent
Model Based Reflex Agent
Goal Based Agent
All of the above
By perceiving the environment through sensors
By human's sensory organs
Both 1) and 2)
None of the above
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
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
Probability
Inference
Heuristic Search
All of the above
A state space can be defined as the collection of all the problem states
A state space is a state which exists in environment which is in outer space
A state space is the total space available for the agent in the state
All of the above
Personal Enhancement Area in Science
Performance, Environment, Actuators and Sensors
Performance, Entity, Area, State
None of the above
Top-down approach
Bottom-up approach
No specific approach
According to precedence
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
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
0
-1
+1
Is decided in prior to every problem
Half true Half False
Somewhat true but not entirely false
Agent has no information about the event
Both a. and b.
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.
N- Queens Problem
Chess
Sudoku
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
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Sensors and Actuators
Wheels and steering
Arms and legs
All of the above
Uncertainty in Environment
Poor battery life of the system
Improper training time
All of the above
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.