MIS 5 INTELLIGENT INFORMATION SYSTEMS 13 BIDGOLI Copyright ©2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted

MIS5

INTELLIGENT INFORMATION SYSTEMS

13

BIDGOLI

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

2Copyright ©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. MIS5 4 | CH13

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 reasoning4 Summarize the types of intelligent

agents and how they are used5 Describe fuzzy logic and its uses

3Copyright ©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. MIS5 | CH13

LEARNING OUTCOMES (continued)

6 Explain artificial neural networks7 Describe how genetic algorithms are

used8 Explain natural-language processing and

its advantages and disadvantages9 Summarize the advantages of

integrating AI technologies into decision support systems

10Explain contextual computing


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


AI Technologies Supporting Decision Making

• Decision makers use information technologies in decision-making analyses of:• What-is – Analysis used in transaction-

processing systems and management information systems

• What-if – Analysis used in decision support systems


Table 13.1 Applications of AI Technologies


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)


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


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


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


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



• 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



• 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



- 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


Exhibit

13.1 An Expert System Configuration


Uses of Expert Systems


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


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


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


Advantages of Expert Systems


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


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)


Characteristics of Intelligent Agents


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


Categories of Available Intelligent Agents


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


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


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


Monitoring and Surveillance Agents

• Track and report on computer equipment and network systems to predict when a system crash or failure might occur


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


Exhibit

13.3 Degree of Membership in a Fuzzy System


Areas Where Fuzzy Logic is Used

• Search engines• Chip design• Database management systems• Software development


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


Exhibit

13.4 Artificial Neural Network Configuration


Tasks Involving the Use of ANNs


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


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


Table 13.2 NLP Systems


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


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


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)


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 and

interpret stimuli


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

KEY TERMS


• Artificial intelligence (AI) • Artificial neural networks (ANNs)• Backward chaining• Case-based reasoning (CBR) • Contextual computing• Data-mining agents• Expert systems • Explanation facility

KEY TERMS


• Forward chaining • Fuzzy logic • Genetic algorithms (GAs)• Inference engine• Intelligent agents• Knowledge acquisition facility • Knowledge base• Knowledge base management system (KBMS)

KEY TERMS


• Monitoring and surveillance agents• Natural-language processing (NLP)• Personal agents• Robots• Shopping and information agents

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

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


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MIS 5 INTELLIGENT INFORMATION SYSTEMS 13 BIDGOLI Copyright ©2016 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted