Module 13: Artificial Intelligence and Automation
DIFFICULTY: Easy
REFERENCES: Explain contextual computing.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.10
TOPICS: Context-aware computing
KEYWORDS: Remember
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
82. consists of related technologies that try to simulate and reproduce human thought behavior, including thinking,
speaking, feeling, and reasoning.
a. Cloud computing
b. Data mining
c. Artificial intelligence
d. Grid computing
ANSWER: c
RATIONALE: Artificial intelligence (AI) consists of related technologies that try to simulate and
reproduce human thought behavior, including thinking, speaking, feeling, and reasoning.
AI technologies apply computers to areas that require knowledge, perception, reasoning,
understanding, and cognitive abilities. See 13-1: What Is Artificial Intelligence?
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Define artificial intelligence, and explain how AI technologies support decision
making.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.1
TOPICS: Artificial intelligence
KEYWORDS: Remember
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
83. In the context of the types of decision-making analyses, what type of analysis is used in decision support systems?
a. case-based
b. what-is
c. what-if
d. rule-based
ANSWER: c
RATIONALE: The what-if analysis is used in decision support systems. Decision makers use it to monitor
the effect of a change in one or more variables. See 13-1: What Is Artificial Intelligence?
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Define artificial intelligence, and explain how AI technologies support decision
making.
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,Module 13: Artificial Intelligence and Automation
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.1
TOPICS: Artificial intelligence
KEYWORDS: Remember
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
84. In the context of the components of a typical expert system, is a software package with manual or automated
methods for acquiring and incorporating new rules and facts so that the expert system is capable of growth.
a. knowledge base
b. monitoring and surveillance agent
c. knowledge acquisition facility
d. personal agent
ANSWER: c
RATIONALE: A knowledge acquisition facility is a software package with manual or automated methods
for acquiring and incorporating new rules and facts so that the expert system is capable of
growth. This component works with the knowledge base management system to ensure
that the knowledge base is as up to date as possible. See 13-2: Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
85. In the context of the components of a typical expert system, is similar to a database, but in addition to storing
facts and figures it keeps track of rules and explanations associated with facts.
a. a knowledge acquisition facility
b. a knowledge base
c. factual knowledge
d. heuristic knowledge
ANSWER: b
RATIONALE: A knowledge base is similar to a database, but in addition to storing facts and figures it
keeps track of rules and explanations associated with facts. For example, a financial expert
system’s knowledge base might keep track of all figures constituting current assets,
including cash, deposits, and accounts receivable. It might also keep track of the fact that
current assets can be converted to cash within one year. See 13-2: Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
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,Module 13: Artificial Intelligence and Automation
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 11/26/2019 2:30 PM
86. A(n) is the component of an expert system that performs tasks similar to what a human expert does by
explaining to end users how recommendations are derived.
a. user interface
b. explanation facility
c. inference engine
d. knowledge base
ANSWER: b
RATIONALE: An explanation facility performs tasks similar to what a human expert does by explaining
to end users how recommendations are derived. For example, in a loan evaluation expert
system, the explanation facility states why an applicant was approved or rejected. See 13-2:
Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
87. In the context of the different techniques used by an inference engine to manipulate a series of rules, refers to a
series of “if-then-else” condition pairs.
a. forward chaining
b. backward chaining
c. inductive reasoning
d. abductive reasoning
ANSWER: a
RATIONALE: In forward chaining, a series of “if-then-else” condition pairs is performed. The “if”
condition is evaluated first, and then the corresponding “then-else” action is carried out.
See 13-2: Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
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, Module 13: Artificial Intelligence and Automation
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 11/26/2019 2:33 PM
88. is a problem-solving technique where each problem in a database is stored with a description and keywords that
identify it.
a. Rule-based reasoning
b. Inductive reasoning
c. Abductive reasoning
d. Case-based reasoning
ANSWER: d
RATIONALE: Expert systems solve a problem by going through a series of if-then-else rules, but case-
based reasoning is a problem-solving technique that matches a new case (problem) with a
previously solved case and its solution, both stored in a database. See 13-3: Case-Based
Reasoning
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe case-based reasoning.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.3
TOPICS: Case-based reasoning
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
89. allows a smooth, gradual transition between human and computer vocabularies and deals with variations in
linguistic terms by using a degree of membership.
a. Fuzzy logic
b. Digital analysis
c. Data mining
d. Finite automata
ANSWER: a
RATIONALE: Fuzzy logic allows a smooth, gradual transition between human and computer vocabularies
and deals with variations in linguistic terms by using a degree of membership. A degree of
membership shows how relevant an item or object is to a set. A higher number indicates it
is more relevant, and a lower number shows it is less. See 13-5: Fuzzy Logic
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe fuzzy logic and its uses.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.5
Copyright Cengage Learning. Powered by Cognero. Page 42
DIFFICULTY: Easy
REFERENCES: Explain contextual computing.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.10
TOPICS: Context-aware computing
KEYWORDS: Remember
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
82. consists of related technologies that try to simulate and reproduce human thought behavior, including thinking,
speaking, feeling, and reasoning.
a. Cloud computing
b. Data mining
c. Artificial intelligence
d. Grid computing
ANSWER: c
RATIONALE: Artificial intelligence (AI) consists of related technologies that try to simulate and
reproduce human thought behavior, including thinking, speaking, feeling, and reasoning.
AI technologies apply computers to areas that require knowledge, perception, reasoning,
understanding, and cognitive abilities. See 13-1: What Is Artificial Intelligence?
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Define artificial intelligence, and explain how AI technologies support decision
making.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.1
TOPICS: Artificial intelligence
KEYWORDS: Remember
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
83. In the context of the types of decision-making analyses, what type of analysis is used in decision support systems?
a. case-based
b. what-is
c. what-if
d. rule-based
ANSWER: c
RATIONALE: The what-if analysis is used in decision support systems. Decision makers use it to monitor
the effect of a change in one or more variables. See 13-1: What Is Artificial Intelligence?
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Define artificial intelligence, and explain how AI technologies support decision
making.
Copyright Cengage Learning. Powered by Cognero. Page 39
,Module 13: Artificial Intelligence and Automation
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.1
TOPICS: Artificial intelligence
KEYWORDS: Remember
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
84. In the context of the components of a typical expert system, is a software package with manual or automated
methods for acquiring and incorporating new rules and facts so that the expert system is capable of growth.
a. knowledge base
b. monitoring and surveillance agent
c. knowledge acquisition facility
d. personal agent
ANSWER: c
RATIONALE: A knowledge acquisition facility is a software package with manual or automated methods
for acquiring and incorporating new rules and facts so that the expert system is capable of
growth. This component works with the knowledge base management system to ensure
that the knowledge base is as up to date as possible. See 13-2: Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
85. In the context of the components of a typical expert system, is similar to a database, but in addition to storing
facts and figures it keeps track of rules and explanations associated with facts.
a. a knowledge acquisition facility
b. a knowledge base
c. factual knowledge
d. heuristic knowledge
ANSWER: b
RATIONALE: A knowledge base is similar to a database, but in addition to storing facts and figures it
keeps track of rules and explanations associated with facts. For example, a financial expert
system’s knowledge base might keep track of all figures constituting current assets,
including cash, deposits, and accounts receivable. It might also keep track of the fact that
current assets can be converted to cash within one year. See 13-2: Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
Copyright Cengage Learning. Powered by Cognero. Page 40
,Module 13: Artificial Intelligence and Automation
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 11/26/2019 2:30 PM
86. A(n) is the component of an expert system that performs tasks similar to what a human expert does by
explaining to end users how recommendations are derived.
a. user interface
b. explanation facility
c. inference engine
d. knowledge base
ANSWER: b
RATIONALE: An explanation facility performs tasks similar to what a human expert does by explaining
to end users how recommendations are derived. For example, in a loan evaluation expert
system, the explanation facility states why an applicant was approved or rejected. See 13-2:
Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
87. In the context of the different techniques used by an inference engine to manipulate a series of rules, refers to a
series of “if-then-else” condition pairs.
a. forward chaining
b. backward chaining
c. inductive reasoning
d. abductive reasoning
ANSWER: a
RATIONALE: In forward chaining, a series of “if-then-else” condition pairs is performed. The “if”
condition is evaluated first, and then the corresponding “then-else” action is carried out.
See 13-2: Expert Systems
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe an expert system, its applications, and its components.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
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, Module 13: Artificial Intelligence and Automation
LEARNING OBJECTIVES: MIS.10e.13.2
TOPICS: Expert system components
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 11/26/2019 2:33 PM
88. is a problem-solving technique where each problem in a database is stored with a description and keywords that
identify it.
a. Rule-based reasoning
b. Inductive reasoning
c. Abductive reasoning
d. Case-based reasoning
ANSWER: d
RATIONALE: Expert systems solve a problem by going through a series of if-then-else rules, but case-
based reasoning is a problem-solving technique that matches a new case (problem) with a
previously solved case and its solution, both stored in a database. See 13-3: Case-Based
Reasoning
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe case-based reasoning.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.3
TOPICS: Case-based reasoning
KEYWORDS: Understand
DATE CREATED: 10/22/2019 1:33 PM
DATE MODIFIED: 10/22/2019 1:33 PM
89. allows a smooth, gradual transition between human and computer vocabularies and deals with variations in
linguistic terms by using a degree of membership.
a. Fuzzy logic
b. Digital analysis
c. Data mining
d. Finite automata
ANSWER: a
RATIONALE: Fuzzy logic allows a smooth, gradual transition between human and computer vocabularies
and deals with variations in linguistic terms by using a degree of membership. A degree of
membership shows how relevant an item or object is to a set. A higher number indicates it
is more relevant, and a lower number shows it is less. See 13-5: Fuzzy Logic
POINTS: 1
DIFFICULTY: Easy
REFERENCES: Describe fuzzy logic and its uses.
QUESTION TYPE: Multiple Choice
HAS VARIABLES: False
LEARNING OBJECTIVES: MIS.10e.13.5
Copyright Cengage Learning. Powered by Cognero. Page 42
