mis 5 intelligent information systems 13 bidgoli copyright ©2016 cengage learning. all rights...
TRANSCRIPT
MIS5
INTELLIGENT INFORMATION SYSTEMS
13
BIDGOLI
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LEARNING OUTCOMES
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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
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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
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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
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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
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Table 13.1 Applications of AI Technologies
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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)
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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
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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
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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
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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
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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
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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
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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
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Exhibit
13.1 An Expert System Configuration
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Uses of Expert Systems
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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
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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
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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
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Advantages of Expert Systems
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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
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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)
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Characteristics of Intelligent Agents
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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
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Categories of Available Intelligent Agents
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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
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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
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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
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Monitoring and Surveillance Agents
• Track and report on computer equipment and network systems to predict when a system crash or failure might occur
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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
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Exhibit
13.3 Degree of Membership in a Fuzzy System
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Areas Where Fuzzy Logic is Used
• Search engines• Chip design• Database management systems• Software development
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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
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Exhibit
13.4 Artificial Neural Network Configuration
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Tasks Involving the Use of ANNs
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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
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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
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Table 13.2 NLP Systems
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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
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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
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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)
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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
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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
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• Artificial intelligence (AI) • Artificial neural networks (ANNs)• Backward chaining• Case-based reasoning (CBR) • Contextual computing• Data-mining agents• Expert systems • Explanation facility
KEY TERMS
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• Forward chaining • Fuzzy logic • Genetic algorithms (GAs)• Inference engine• Intelligent agents• Knowledge acquisition facility • Knowledge base• Knowledge base management system (KBMS)
KEY TERMS
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• Monitoring and surveillance agents• Natural-language processing (NLP)• Personal agents• Robots• Shopping and information agents
SUMMARY
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• 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
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• 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