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
B. Quantifiers are the quantity defining terms which are used with the predicates.
Half true Half False
Somewhat true but not entirely false
Agent has no information about the event
Both a. and b.
Encryption Problem
Constraint Satisfactory Problem
Number problem
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
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.
All i, ii. and iii.
By perceiving the environment through sensors
By human's sensory organs
Both 1) and 2)
None of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
i. v. ii. iv. iii.
i. ii. iii. iv. v.
ii. i. v. iv. iii.
None of the above
Forward Chaining
Backward Chaining
Both a. and b.
None of the above
Only valid data
Only invalid data
Both valid and invalid data
None of the above
3 levels
2 levels
4 levels
None of the above
Uncertainty in Environment
Poor battery life of the system
Improper training time
All of the above
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
Left sided and right sided
Personal Enhancement Area in Science
Performance, Environment, Actuators and Sensors
Performance, Entity, Area, State
None of the above
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
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
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii. and iv.
Reverend Thomas Bayes
Stuart Bayes Hamilton
Bayes Canney
None of the above.
It is the way in which facts and information are stored in the storage system of the agent
It is the way in which we feed the knowledge in machine understandable form
We modify the knowledge and convert it into the format which is acceptable by the machine
All of the above
Sky and Land
Agent and environment
Yes or No
None 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
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Knowledge gathering strategy
Final step of solving the AI problem, which is applying the strategies
State space deciding
None of the above
Thinking
Eating
Sleeping
None of the above
Only iv.
All i., ii., iii. and iv.
ii. and iv.
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
Discrete or Continuous
Observable and partially-observable
Static and dynamic
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.
To share passwords
To encode number plates of vehicles
To encode their names by students while filling the answer sheet
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.