AI00 2nd Quiz file

NATURAL LANGUAGE GENERATION (NLG) acts as a translator that converts the

computerized data into natural language representation.

Learning is a very active and large area of AI research.

Data features while performing the machine learning process is also called Row.

Learning can be called as normally a relatively permanent change that occurs in behavior

because of experience.

Remote Controlled Robots used for performing complicated and undetermined tasks that

autonomous robot cannot perform due to uncertainty of operation

AI is not a system. True

Features are simply the columns of the table called Labels.

ML is the learning in which machine can learn on its own without being explicitly

programmed to do so.

A/An expert systems can be defined as a software program that can outline reasoned

conclusions from an amount of knowledge in a specific domain and aims to develop “smart”

program and applications.

A consequent is a fuzzy set represented by a membership function, which weighs

appropriately the linguistic characteristics that are attributed to it.

Which is not a conflict resolution strategy? Fire last rule in sequence

The negation of converse is termed as contra positive, and It can be represented as ~ Q ~ →

P

An Expert system is a computer system that uses the decision making capability of a/an

Inference Engine.

Supervised learning data comes with description, labels, targets or desired

outputs and the objective is to find a general rule that maps inputs to

outputs

Regression : These types of models predict a number, Trains on and predicts a continuousvalued response.

Refers to partitioning attributes such that they may become more useful to a machine

learning technique.

The one component of AI agent include that direct mapping from conditions on the current

state to actions.

Fuzzy inference system (FIS) is the process of formulating the mapping from a given input

to an output using fuzzy logic

Backward chaining is Goal Driven Approach.

ML or machine learning is to build computer systems that can learn from their experience

and adapt to their environments.

FEATURE SELECTION It is essentially filtering- and refers to the selection of a subset of the

original example set that is most relevant in the predictive modeling at hand.

Controller is a part of robot that coordinates all motion of the mechanical system.

ML has become a rapidly growing subset of AI research.

ML involves in creating Self-Learning algorithms.

Inference Engine consists of all processes that manipulate the knowledge base to deduce

information requested by the user and carries the reasoning required by the expert system

to reach a solution.

Quantifiers in First-order logic: Symbols that permit to determine or identify the range and

scope of the variable in a logical expression.

It is a supervised learning task where output is having defined labels(discrete Value).

Classifications

Modus Ponens : If P is True and P Q is also True, then we can infer that Q will be →

True.

Classify accuracy refers at which system performs the task of classification.

Machine Learning Is primarily concerned with the design and development of algorithms

that allow the system to learn from historical data.

Semantic Network Representation Alternative of predicate logic for knowledge

representation.

An intelligent agent needs knowledge about the real world for taking decisions and

reasoning to act efficiently.

A/An Classical set is a container, which wholly includes or excludes any given statement.

Conflict resolution occurs when the premises of two rules match the given facts. Which

should be fired first? If we fire both, they may add conflicting facts.

A set of Rules contains all actions that should be taken within the scope of a problem

specify how to act on the assertion set.

Universal Quantifier is a symbol of logical representation, which specifies that the

statement within its range is true for everything or every instance of a thing.

NATURAL LANGUAGE UNDERSTANDING (NLU) helps the machine to understand and

analyze human language by extracting the metadata from the content such as concepts,

entities, keywords, emotions, relations, and semantic roles.

One of the earliest expert systems DENDRAL was developed at stanford University.

DENDRAL and Xcon are Rule driven reasoning models.

Forward chaining is Facts Approach.

Syntax is the rule which decide how we can construct legal sentences in the logic.

The inference engine can match the facts contained in the working memory with the

domain knowledge contained in the knowledge base, to draw conclusions about the

problem.

Fuzzy Logic is a super-set of Boolean logic that has been extended to handle the concept

of partial truth-truth values between completely true and completely false.

Learning is the process of converting experience into Knowledge.

In rote learning there is no need to Prior Knowledge.

Aggregation is the process by which the fuzzy sets that represent the output of each rule

are combined into a single fuzzy set.

Mobile Robots an automatic machine that can navigate an uncontrolled

environment.

Deductive learning memorizes the logical consequences and doesn’t generate new

knowledge at all.

Which is not a way to classify the rules in rule-based systems?

Events

The degree of truth in fuzzy logic is specifically driven out by a function called the

Membership function.

Knowledge level is the one level of knowledge based agent, and in this level we need to

specify what the agent knows and what the agent goals are.

Actuators are the energy conversion devices used inside a robot.

WORD TOKENIZATION is used to break the sentence into separate words or tokens.

1. In rote learning, there is no need to ------------- knowledge.

• Prior

• Current

• Implicit

• Explicit

2. Learning is considered as ------------- and large area of AI research

• In Active

• Active

• Passive

• Direct

3. ----------is a part of robot that coordinates all motion of the mechanical system.

• Controller

• Actuators

• Effectors

• Sensors

4. An intelligent agent needs knowledge about the real world for -------- to act efficiently.

• Calculations

• Knowledge representation

• Taking decisions and reasoning

• Problem solving

5. ----------- acts as a translator that converts the computerized data into natural languages

representation.

• NLG

• NLU

6. One of the earliest expert systems -------- was developed at Stanford university.

• DENDRAL

• MYCIN

• PROSPECTOR

• XCON

7. ML is the learning in which machine can learn on its own without being ---------- programmed.

• Implicitly

• Explicitly

8. There are two ways for a rule to set new values for the data:

• Assignment and assertion

• Assignment and dynamic allocation

• Assertion and fixed

• Fixed and variable

9. Backward chaining is ------- approach.

• Goal driven

• Facts driven

• Knowledge driven

• Rule driven

10. Semantic networks are alternative of ------------ for knowledge representation

• Predicate logic

• Formal Logic

• Propositional Logic

• First order Logic

11. ------------- is primarily concerned with the design and development of algorithms that allow the

system to learn from historical data.

• Machine learning

• Robotics

• Rule based systems

• Expert systems

12. AI is not a system

• True

• False

13. ---------- are the energy conversion device used inside a robot.

• Actuators

• Effectors

• Sensors

• Controller

14. The inference engine can match the facts contained in the --------- with the domain knowledge

contained in the knowledge base, to draw conclusions about the problem.

• Working memory

• Processor

• CPU

• RAM

15. DENDRAL and XCON/R are ----------- reasoning models.

• Facts driven

• Goal driven

• Rule driven

• Event driven