Welcome to the Knowledge and Reasoning MCQs Page

Dive deep into the fascinating world of Knowledge and Reasoning with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Knowledge and Reasoning, a crucial aspect of Artificial Intelligence. In this section, you will encounter a diverse range of MCQs that cover various aspects of Knowledge and Reasoning, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Artificial Intelligence.

Check out the MCQs below to embark on an enriching journey through Knowledge and Reasoning. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Artificial Intelligence.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Knowledge and Reasoning. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Knowledge and Reasoning MCQs | Page 4 of 9

Explore more Topics under Artificial Intelligence

01

Introduction to AI

02

Intelligent Agents

03

Problem Solving

04

Game Planning

05

Uncertain Knowledge

06

Learning

07

Perceiving and Acting

08

Natural Language Processing

09

LISP Programming

10

Expert Systems

Q31.

The CAI (Computer-Assisted Instruction) technique based on programmed instruction is:

frame-based CAI

generative CAI

problem-solving CAI

intelligent CAI

Discuss

Answer: (a).frame-based CAI

Q32.

Computers normally solve problem by breaking them down into a series of yes-or-no decisions represented by 1s and 0s. What is the name of the logic that allows computers to assign numerical values that fail somewhere between 0 and 1?

Human logic

Fuzzy logic

Boolean logic

Operational logic

Discuss

Answer: (b).Fuzzy logic

Q33.

The component of an ICAI (Intelligent Computer-Asslsted Instruction) presenting information to the student is the:

student model

problem-solving expertise

tutoring module

All of the above

Discuss

Answer: (c).tutoring module

Q34.

The Newell and Simon program that proved theorems of Principia Mathematica was:

Elementary Perceiver

General Problem Solver

Logic Theorist

Boolean Algebra

Discuss

Answer: (c).Logic Theorist

Q35.

Shaping teaching techniques to fit the learning patterns of individual students is the goal of:

decision support

automatic programming

intelligent computer-assisted instruction

expert systems

Discuss

Answer: (c).intelligent computer-assisted instruction

Q36.

What is Fuzzy Logic?

a method of reasoning that resembles human reasoning

a method of question that resembles human answer

a method of giving answer that resembles human answer.

None of the Above

Discuss

Answer: (a).a method of reasoning that resembles human reasoning

Q37.

How many output Fuzzy Logic produce?

Discuss

Answer: (a).2

Q38.

Fuzzy Logic can be implemented in?

Hardware

software

both a and b

None of the Above

Discuss

Answer: (c).both a and b

Q39.

The truth values of traditional set theory is ____________ and that of fuzzy set is __________

Either 0 or 1, between 0 & 1

Between 0 & 1, either 0 or 1

Between 0 & 1, between 0 & 1

Either 0 or 1, either 0 or 1

Discuss

Answer: (a).Either 0 or 1, between 0 & 1

Q40.

How many main parts are there in Fuzzy Logic Systems Architecture?

Discuss

Answer: (b).4

Page 4 of 9

Welcome to the Knowledge and Reasoning MCQs Page

Knowledge and Reasoning MCQs | Page 4 of 9

Explore more Topics under Artificial Intelligence

Introduction to AI

Intelligent Agents

Problem Solving

Game Planning

Uncertain Knowledge

Learning

Perceiving and Acting

Natural Language Processing

LISP Programming

Expert Systems

Suggested Topics

Data Structures and Algorithms

Python

R Programming

Software Architecture and Design

MATLAB

Java Spring Framework

UNIX

Java Programming

CSS