Which of the following definitions correctly defines the State-space in an AI system?
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
Correct Answer :
A. A state space can be defined as the collection of all the problem states
All the possible states for an AI system together form the state space. The state-space means the collection of all those states in which the agent can be.
Related Questions
What do the Constraints refer to in a CSP (Constraint Satisfactory problem)?
Restrictions
Rules
Regulations
All of the above
Which of the following mentioned statements are the valid reasons for implementing the learning part in the systems in AI?
To implement humanly behavior.
To deal with unknown environment.
To improve the reasoning capability of the agent.
All of the above
Which if the following are valid inference rules that are used in Inference?
a) Addition
b) Subtraction
c) Multiplication
d) Division
Options:
Only i.
i. and iii.
ii. and iii.
iii. and iv.
Consider the following statement:When we talk about perceiving information from the environment, then the main problem that arises is that there is always some uncertainty is our observations. This is because the world is an enormous entity and the surroundings that we take under study are not always well defined. So, there is needs to be an estimation taken for getting to any conclusion.Which among the following takes the best decisions in a situation with uncertainty?
AI based agents
Humans
Animals
None of the above
Which of the mentioned human behavior does the AI aim to mimic?
Thinking
Eating
Sleeping
None of the above
In AI, the Logic is classified into two types: deductive and inductive. Which of the following approaches is followed up by the Inductive logic?
Top-down approach
Bottom-up approach
No specific approach
According to precedence
Which of the following classifications of the environment are valid?
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above
Consider the following statement:The value of the Certainty factor lies between -1.0 to +1.0, where the negative 1.0 value suggests that the statement can never be true in any situation, and the positive 1.0 value defines that the statement can never be false.What does the value 0 denote for CF?
Half true Half False
Somewhat true but not entirely false
Agent has no information about the event
Both a. and b.
How does the agent learn through its surroundings?
By perceiving the environment through sensors
By human's sensory organs
Both 1) and 2)
None of the above
The Certainty Factor (CF) is a numeric value which tells us about how likely an event or a statement is supposed to be true.What is the range of this numeric value, i.e. Certainty Factor?
Between 0 to 1 (Both inclusive)
Between 0 to 1 (Both exclusive)
Between -1 to +1
None of the above
In AI systems, Logic can be represented in two types. What are these two types?
a) Inductive Logic
b) Common Logic
c) Deductive Logic
d) Machine Logic
Options:
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Which of the following mentioned searches are heuristic searches?
a) Random Search
b) Depth First Search
c) Breadth First Search
d) Best First Search
Options:
Only iv.
All i., ii., iii. and iv.
ii. and iv.
None of the above
Which of the following mentioned properties are valid for a Cryptarithmetic problem?
a) A number 0-9 is assigned to a particular alphabet.
b) Each different alphabet has a unique number.
c) All the same alphabets have the same numbers.
d) The numbers should satisfy all the operations that any normal number does.
Options:
Only iv.
All i., ii., iii. and iv.
ii. and iv.
None of the above
There are two types of quantifiers used to quantify the statement in the knowledge representation in AI. What are these two types of quantifiers?
a) Universal Quantifiers
b) Subjective Quantifiers
c) Existential Quantifiers
d) Selective Quantifiers
Options:
i. and ii.
i. and iii.
ii. and iii.
iii. and iv.
Which of the mentioned rules are valid Inference rules?
Modus Ponens
Resolution
Backward Chaining
All of the above
Which of the levels in a knowledge-based agent is the most abstract level?
Knowledge Level
Logical Level
Implementation Level
Can't be determined
Which of the following mentioned statements are uncertain?
a) The number occurred on rolling a die.
b) What will the temperature tomorrow?
c) What card will be get on picking a card from a fair deck of 52 cards?
d) What output will we get on tossing a coin?
Options:
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
Which of the following statements correctly define the concept of Inference in AI?
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.
Which of the following are a part of Fuzzy Logic System? Choose from the following options?
a) Knowledge base
b) Fuzzification Module
c) Inference Engine
d) Defuzzification Module
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii. and iv.
Which if the following are valid methods used for decision making by an AI agent in situations of uncertainty? Choose from the following options?
a) Probabilistic theory
b) Fuzzy logic
c) Truth Maintenance
Only i.
i. and iii.
ii. and iii.
All i, ii. and iii.
Which of the following agents is the best in terms of AI?
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
In which of the following mentioned statements, probabilistic reasoning is applicable?
a) The number occurred on rolling a die.
b) What will the temperature tomorrow?
c) What card will get on picking a card from a fair deck of 52 cards?
d) What output will we get on tossing a coin?
Options:
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
Which of the following statements define the certainty factor accurately?
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
Which of the following points are valid with respect to conditional probability?
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.
Among which of the following mentioned statements can the Bayesian probability be applied?
a) In the cases, where we have one event
b) In the cases, where we have two events
c) In the cases, where we have three events
d) In the cases, where we have more than three events
Options:
Only iv.
All i., ii., iii. and iv.
ii. and iv.
Only ii.
On which of the mentioned points does the Probabilistic Reasoning depend?
Estimation
Likelihood
Observations
All of the above
Consider the following statement:The Cryptarithmetic problem in Artificial Intelligence is a type of encryption problem in which the written message in an alphabetical form which is easily readable and understandable is converted into a numeric form which is neither easily readable nor understandable.By reading the above statement, what are the places where this technique can be applied?
To share passwords
To encode number plates of vehicles
To encode their names by students while filling the answer sheet
None of the above
Which of the mentioned Environment Classifications determine whether the environment variables are constant or keep changing?
Deterministic and non- Deterministic
Observable and partially-observable
Static and dynamic
All of the above
Why do we want to implement the concept of Logic in an AI system?
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
The results that we get after we apply conditional probability to a problem are,
100% accurate
Estimated values
Wrong values
None of the above