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
D. All of the above
Only i.
i. and iii.
ii. and iii.
iii. and iv.
Responding and providing solution to the problem
Meeting the preference of the user
Meeting the goal
All 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
Dependent Events
Independent Events
Neither a. nor b.
Both a. and b.
3 levels
2 levels
4 levels
None of the above
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
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
Simple based reflex agent
Model based reflex agent
Goal based agent
Utility based agent
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
Between 0 to 1 (Both inclusive)
Between 0 to 1 (Both exclusive)
Between -1 to +1
None of the above
By perceiving the environment through sensors
By human's sensory organs
Both 1) and 2)
None of the above
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Perceiving data from the environment
Adapting to the environment and situations
Acting upon the Environment
Reversing the previously performed actions
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii. and iv.
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 valid data
Only invalid data
Both valid and invalid data
None of the above
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All 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
Personal Enhancement Area in Science
Performance, Environment, Actuators and Sensors
Performance, Entity, Area, State
None of the above
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.
The Breadth First Search (BFS)
The Depth First Search (DFS)
The A* search
None of the above
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Probability
Inference
Heuristic Search
All of the above
Sensors and Actuators
Wheels and steering
Arms and legs
All of the above
N- Queens Problem
Chess
Sudoku
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
Knowledge Level
Logical Level
Implementation Level
Can't be determined
Knowledge Level
Logical Level
Implementation Level
Can't be determined
Encryption Problem
Constraint Satisfactory Problem
Number problem
All of the above
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.