Principles of Information Systems (MindTap Course List)
Principles of Information Systems (MindTap Course List)
13th Edition
ISBN: 9781337516945
Author: STAIR
Publisher: Cengage
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Chapter 10, Problem 15RQ
Program Plan Intro

Artificial Intelligence:

Artificial Intelligence (AI) simulates thinking and behaves as human such as the capability of giving reason and learning.

  • Its main aim is to develop a system which mimics human intelligence.
  • It increases the speed and consistency of decision making, helps in solving the problems without lending complete information.
  • The problems which cannot be solved by the conventional computing can be resolved using the AI system.

Components of Artificial Intelligence:

The six key components of AI are as follows:

  • Expert systems: A work performed by a human expert and the same task is performed by a computer application is known as expert systems.
  • Robotics: It is a nothing but a development of computer devices that can perform tasks that are difficult for humans which requires higher precision.
  • Vision systems: A hardware or a software program that allows the processor (computer) to capture, store and process visual images.
  • Natural language processing: As the name suggests, it allows the processor to infer and respond to the statements and commands (human level) that are given in natural language like English.
  • Learning systems: It is an integration of software and hardware that permits the processor to change how it functions and how it responds to certain conditions based on comment it collects.
  • Neural networks: Neural network is also called as artificial neural network where the AI attempts to imitate the way human brain works.

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Refer to page 80 for problems on white-box testing. Instructions: • Perform control flow testing for the given program, drawing the control flow graph (CFG). • Design test cases to achieve statement, branch, and path coverage. • Justify the adequacy of your test cases using the CFG. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS3IZ9qo Hazb9tC440 AZF/view?usp=sharing]
Refer to page 10 for problems on parsing. Instructions: • Design a top-down parser for the given grammar (e.g., recursive descent or LL(1)). • Compute the FIRST and FOLLOW sets and construct the parsing table if applicable. • Parse a sample input string and explain the derivation step-by-step. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qoHazb9tC440 AZF/view?usp=sharing]
Refer to page 20 for problems related to finite automata. Instructions: • Design a deterministic finite automaton (DFA) or nondeterministic finite automaton (NFA) for the given language. • Minimize the DFA and show all steps, including state merging. • Verify that the automaton accepts the correct language by testing with sample strings. Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qo Hazb9tC440AZF/view?usp=sharing]

Chapter 10 Solutions

Principles of Information Systems (MindTap Course List)

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