MIS BIDGOLI 6 13 INTELLIGENT INFORMATION SYSTEMS Copyright

MIS BIDGOLI 6 13 INTELLIGENT INFORMATION SYSTEMS Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

LEARNING OUTCOMES 1 Define artificial intelligence, and explain how AI technologies support decision making 2 Describe an expert system, its applications, and its components 3 Describe case-based reasoning 4 Summarize the types of intelligent agents and how they are used 5 Describe fuzzy logic and its uses Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 2

LEARNING OUTCOMES (continued) 6 Explain artificial neural networks 7 Describe how genetic algorithms are used 8 Explain natural-language processing and its advantages and disadvantages 9 Summarize the advantages of integrating AI technologies into decision support systems 10 Explain contextual computing Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 3

What Is Artificial Intelligence? • Artificial intelligence (AI) • Consists of related technologies that try to simulate and reproduce human thought and behavior • Includes thinking, speaking, feeling, and reasoning • AI technologies • Involve computer application to areas that require knowledge, perception, reasoning, understanding, and cognitive abilities • Concerned with generating and displaying knowledge and facts Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 4

AI Technologies Supporting Decision Making • Decision makers use information technologies in decision-making analyses of: • What-is – Analysis used in transactionprocessing systems and management information systems • What-if – Analysis used in decision support systems Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 5

Table 13. 1 Applications of AI Technologies Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 5 | CH 13 6

Robots • Involve application of AI • Excel at performing simple, repetitive tasks • Free workers from tedious or hazardous jobs • Have limited mobility • Operation is controlled by a computer program that includes commands • Includes programming languages for controlling • Variable Assembly Language (VAL) Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 7

Robots • Use following programming languages • Variable Assembly Language (VAL) • Functional Robotics (FROB) • A Manufacturing Language (AML) • Honda’s Advanced Step in Innovative Mobility (ASIMO) • Most advanced and most popular robots • Coordinates with other robots • Personal robots: Posses limited mobility, vision, and speech capabilities Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 8

Robotics • Advantages of robots over humans in the workplace • Never fall in love with coworkers, get insulted, or call in sick • Are consistent • Used in environments that are hazardous to humans • Risk of spying for competitors, asking for a raise, or lobbying for longer breaks does not exist Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 9

Expert Systems • Mimics human expertise in a field to solve a problem in a well-defined area • Used for activities that human experts have already handled successfully • Tasks in medicine, geology, education, and oil exploration • Work with heuristic data which encourages applying knowledge based on experience to solve or describe a problem Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 10

Components of an Expert System • Knowledge acquisition facility • Software package • Has manual or automated methods for acquiring and incorporating new rules and facts so the expert system is capable of growth • Knowledge base • Similar to a database, but in addition to storing facts and figures it keeps track of rules and explanations associated with facts • Includes factual, heuristic, meta types of knowledge Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 11

Components of an Expert System • Knowledge base management system (KBMS) • Similar to a DBMS • Used to keep the knowledge base updated, with changes to facts, figures, and rules • User interface: Provides user-friendly access to the expert system Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 12

Components of an Expert System • Explanation facility • Performs tasks similar to what a human expert does by explaining to end users how recommendations are derived • Inference engine • Similar to the model base component of a decision support system • Uses techniques of forward and backward chaining to manipulate a series of rules Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 13

Components of an Expert System - Forward chaining: Series of “if-then-else” condition pairs is performed - Backward chaining: Expert system starts with the goal and backtracks to find the right solution Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 14

Exhibit 13. 1 An Expert System Configuration Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 5 | CH 13 15

Uses of Expert Systems Forensics lab work Banking and finance Education Food industry Personnel management Security US Government Agriculture Airline industry Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 16

Criteria for Using Expert Systems • Experience and knowledge of several experts is available • Knowledge can be represented as rules or heuristics • Decision or task has already been handled successfully by human experts • Decision or task requires consistency and standardization Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 17

Criteria for Using Expert Systems • Subject domain is limited • Decision or task involves many rules and complex logic • Involves scarcity of experts in the organization Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 18

Criteria for Not Using Expert Systems • Very few rules are involved • Existence of too many rules that slow down the processing capability to unacceptable levels • Well-structured numerical problems involved • Broad range of topics is involved, but there are not many rules • Disagreement among experts Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 19

Advantages of Expert Systems Never become distracted, forgetful, or tired Duplicate and preserve the expertise of scarce experts Preserve the expertise of retiring or relieving employees Create consistency in decision making Improve the decision-making skills of nonexperts Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 20

Case-Based Reasoning • Problem-solving technique that matches a new case with a previously solved case and its solution, stored in a database • Offers a solution after searching for a match • Failing to find a match, human expert is required to solve the problem Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 21

Intelligent Agents • Software capable of reasoning and following rule-based processes • Popular in e-commerce • Known as: • Bots (short for robots) • Virtual agents (VAs) • Intelligent virtual agents (IVAs) Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 22

Characteristics of Intelligent Agents Adaptability Autonomy Collaborative behavior Humanlike interface Mobility Reactivity Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 23

Applications of Intelligent Agents • Web marketing: Collecting following information about customers • Items purchased • Demographic information • Expressed and implied preferences • Virtual catalogs • Display product descriptions based on customers’ previous experiences and preferences Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 24

Categories of Available Intelligent Agents Shopping and information Personal Data-mining Monitoring and surveillance Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 25

Shopping and Information Agents • Help users navigate through the vast resources available on the Web • Provide better results in finding information • Serve as: • Search engines • Site reminders • Personal surfing assistants Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 26

Personal Agents • Perform specific tasks for a user • Remembering information for filling out Web forms • Completing e-mail addresses after the first few characters are typed • Tasks performed by e-mail personal agent • Generate auto-response messages • Forward incoming messages • Create e-mail replies based on the content of incoming messages Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 27

Data-Mining Agents • Work with a data warehouse • Detect trends and discover information and relationships among data items that were not readily apparent • Helps detect potential problems that may arise in future which enables to come up with a solution that minimizes the negative effects of the problem Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 28

Monitoring and Surveillance Agents • Track and report on computer equipment and network systems to predict when a system crash or failure might occur Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 29

Fuzzy Logic • Allows a smooth, gradual transition between human and computer vocabularies • Deals with variations in linguistic terms by using a degree of membership • Designed to help computers simulate vagueness and uncertainty in common situations • Works based on the degree of membership in a set Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 30

Exhibit 13. 3 Degree of Membership in a Fuzzy System Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 5 | CH 13 31

Areas Where Fuzzy Logic is Used • • Search engines Chip design Database management systems Software development Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 32

Artificial Neural Networks (ANNs) • Networks that learn and are capable of performing tasks that are difficult with conventional computers • Playing chess, recognizing patterns in faces and objects, and filtering spam e-mail • Used for poorly structured problems • Use patterns instead of the if-then-else rules used by the expert systems • Create a model based on input and output Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 33

Exhibit 13. 4 Artificial Neural Network Configuration Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 5 | CH 13 34

Tasks Involving the Use of ANNs Bankruptcy prediction Credit rating Investment analysis Oil and gas exploration Target marketing Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 35

Genetic Algorithms (GAs) • Search algorithms that mimic the process of natural evolution • Used to generate solutions to optimization and search problems using mutation, selection, crossover, and chromosome techniques • Designed to find the combination of inputs that generate the most desirable outputs Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 36

Natural Language Processing (NLP) • Developed so that users can communicate with computers in human language • Provides question-and-answer setting that’s natural and easier for people to use • Useful with databases • Use for: • Call routing • Stock and bond trading • Banking by phone Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 37

Table 13. 2 NLP Systems Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 5 | CH 13 38

Categories in NLP Systems • Interface to databases • Machine translation • Text scanning and intelligent indexing programs for summarizing large amounts of text • Generating text for automated production of standard documents • Speech systems for voice interaction with computers Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 39

Activities Performed by NLP Systems • Interfacing • Accepting human language as input • Carrying out the corresponding command • Generating the necessary output • Knowledge acquisition • Using the computer to read large amounts of text and understand the information • Summarize important points and store information so the system can respond to inquiries about the content Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 40

Integrating AI Technologies into Decision Support Systems • AI technologies help improve the quality of decision support systems (DSSs) • Adds explanation capabilities by integrating expert systems and learning capabilities by integrating ANNs • Creates an interface that is easier to use by integrating an NLP system - Systems are called integrated DSSs (IDSSs) Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 41

Contextual Computing • Computing environment that is always present and is capable perceive the surroundings and offer recommendations based on individual need and requirement • Based on the principle that computers can both sense and react to the environments • Similar to how human brains understand interpret stimuli Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 42

Contextual Computing • Allows for tailoring a course of action to a user in a situation and environment based on what it knows about the user • Achieved by using the information technologies • • • Computer networks Software Hardware Database systems AI technologies Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 43

KEY TERMS • Artificial intelligence (AI) • Artificial neural networks (ANNs) • Backward chaining • Case-based reasoning (CBR) • Contextual computing • Data-mining agents • Expert systems • Explanation facility Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 44

KEY TERMS • Forward chaining • Fuzzy logic • Genetic algorithms (GAs) • Inference engine • Intelligent agents • Knowledge acquisition facility • Knowledge base management system (KBMS) Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 45

KEY TERMS • Monitoring and surveillance agents • Natural-language processing (NLP) • Personal agents • Robots • Shopping and information agents Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6 | CH 13 46

SUMMARY • Artificial intelligence technologies apply computers to areas that require knowledge, perception, reasoning, understanding, and cognitive abilities • Intelligent agents are becoming more popular, especially in e-commerce • Fuzzy logic is designed to help computers simulate vagueness and uncertainty in common situations Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6| CH 13 47

SUMMARY • Genetic algorithms examine complex problems without any assumptions of what the correct solution should be • Size and complexity of the human language has made developing NLP systems difficult • Contextual computing allows for tailoring a course of action to a user in a situation and environment based on its knowledge about the user Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 6| CH 13 48

Copyright © 2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. MIS 5 | CH 13 49