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Specialized Business Information Systems
Chapter 7
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The Nature of Intelligence
• Learn from experience & apply the knowledge– Deep Blue improves its performance by playing with
humans
• Handle complex situations– Traffic problem in Istanbul
• Solve problems when important information is missing– Based on available information
• Determine what is important– Choose which facts to use to compute the solution
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The Nature of Intelligence
• React quickly and correctly to new situations – Requires understanding the new situation
• Understand visual images– Requires perception
• Process and manipulate symbols– Computers are better at dealing with numbers
• Be creative and imaginative• Use heuristics
– Rules of thumb from experience
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A comparison of Natural and Artificial Intelligence
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A Conceptual Model of Artificial Intelligence
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What is an Expert System?
• Hardware and software that contain knowledge and manipulate knowledge by inferences
• Mycin (Shortliffe 1976): Expert system for medicine
– Program for advising physicians on treating bacterial infections
– Question and answer dialogues with user– Accounts for uncertainties– Explains its reasoning
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Characteristics of an Expert System
• Can explain their reasoning or suggested decisions– Why recommend a certain medicine?
• Can display “intelligent” behavior • Can draw conclusions from complex relationships
– A patient is diagnosed with two diseases, – The cures for the diseases may have conflicts
• Can provide portable knowledge– Capture knowledge in one’s brain
• Can deal with uncertainty– A patient is diagnose without running all the tests
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Characteristics of an Expert System
• Not widely used or tested • Limited to relatively narrow problems• Cannot readily deal with “mixed” knowledge
– Expert systems should talk to each other
• Cannot refine its own knowledge– Should be able to keep a consistent knowledgebase– Should have a way to gain new knowledge
• May have high development costs• Raise legal and ethical concerns
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When to Use Expert Systems
• High payoff• Preserve scarce expertise• Provide more consistency than humans• Faster solutions than humans• Training expertise
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Components of an Expert System
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The Relationships Among Data, Information, and Knowledge
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Rules for a Credit Application
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The Knowledge Acquisition Facility
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Knowledge Base
• Assembling human experts– Combine knowledge from several experts– Disagree on many items
• The use of fuzzy logic– For relations that are not precise– Is a 50-year old man old? – Help computers deal with imprecise
knowledge– Ex: Washing machines; Auto-focus cameras
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Knowledge Base
• The use of rules– Rule: Conditional statement (if … then)– If the condition matches, the action fires– More rules generally mean more precision
• The use of cases– Template of problems or situations– To find the solution of a new case, find similar
old cases and apply result
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Inference Engine (1)
• Use information and relations to derive new facts to solve problems or predict possible outcomes
• Main reasoning component• Find the right facts, apply the right relations, etc.• Ex: Facts: male(Ali), female(Oya) • Relations: father(X, Y) => male(X)• The engine can conclude that Oya cannot be a
father.
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Inference Engine (2)
• Backward chaining– You start with conclusions– You want to find out if you can get to the conclusion
from your facts
• Forward chaining– You start with facts and try to reach conclusions– More expensive since it can generate many
conclusions
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Other Components
• Explanation Facility– Enables the expert system to explain its reasoning– Helps the user to judge the expert system
• Knowledge Acquisition Facility– Get and update knowledge– Provide a way to capture and store knowledge– Can be semi-automated
• User Interface– Help users interact with the system– Improve usability
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Expert Systems Development
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Participants in Developing and Using Expert Systems
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Domain Expert
• Recognize the real problem• Develop a general framework for problem solving• Formulate theories about the situation• Develop and use general rules to solve a problem• Know when to break the rules or general principles• Solve problems quickly and efficiently
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Other participants
• Knowledge Engineer– Works in design and implementation of the expert
system– Has considerable information about expert systems
• Knowledge User– End user who will benefit from the system– No need to know anything about expert systems– Can help in testing
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Expert Systems Development Alternatives
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Applications of Expert System and Artificial Intelligence
• Credit granting and loan analysis• Stock Picking• Catching cheats and terrorists
– NORA (Non-obvious Relationship Awareness)
• Budgeting
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Applications of Expert System and Artificial Intelligence
• Games: Proverb solves crossword puzzles• Writing: Evaluate and rate writings• Information management and retrieval• Virus detection
– Learns the actions of a virus
• Hospitals and medical facilities
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Virtual Reality
Enables one or more users to move and react in a computer-simulated environment
• Immersive virtual reality - user becomes fully immersed in an artificial, three-dimensional world that is completely generated by a computer
• Virtual reality system - enables one or more users to move and react in a computer-simulated environment
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Interface Devices
• Head mounted display (HMD)• Binocular Omni-Orientation Monitor (BOOM)• CAVE
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The BOOM, a Head-Coupled Display Device
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Viewing the Detroit Midfield Terminal in an Immersive CAVE System
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Useful Applications
• Medicine – used to link stroke patients to physical therapists
• Education and training – used by military for aircraft maintenance
• Entertainment – Star Wars Episode II: Attack of the Clones
• Real Estate Marketing and Tourism– Used to increase real estate sales– Virtual reality tour of the White House
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Segway
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Robotics
• Mechanical or computer devices that can move autonomously
• Manufacturers use robots to assemble or paint products
• Asimo in Istanbul: Shake hands, dance
• Unmanned Combat Air Vehicles (UCAVs): Identify and destroy targets without human intervention
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Vision Systems
• Capture, store, manipulate visual images
• Fingerprint analysis: Store a database of fingerprints and information about the owners.
• Match a fingerprint with an existing entry in the database
• Mostly recognize black and white
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Natural Language Processing
• Understand and react to statements in natural language
• Three levels of understanding– Commands– Discrete– Continuous
• Talk to a computer; computer converts languages to commands understandable by computers
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Learning Systems
• Change its behavior over time– Computer takes an action– User gives feedback– Based on the feedback, computer modifies its
action
• First train the system; then try on test data
• Amazon.com learns user models as users browse and buy goods
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Summary
• Artificial intelligence - used to describe computers with ability to mimic or duplicate functions of the human brain
• Intelligent behavior - includes the ability to learn from experience
• Expert systems - can explain their reasoning (or suggested decisions) and display intelligent behavior
• Virtual reality system - enables one or more users to move and react in a computer-simulated environment
• Special-purpose systems - assist organizations and individuals in new and exciting ways
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Principles and Learning Objectives
• Artificial intelligence systems form a broad and diverse set of systems that can replicate human decision making for certain types of well-defined problems.
– Define the term artificial intelligence and state the objective of developing artificial intelligence systems.
– List the characteristics of intelligent behavior and compare the performance of natural and artificial intelligence systems for each of these characteristics.
– Identify the major components of the artificial intelligence field and provide one example of each type of system.
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Principles and Learning Objectives
• Expert systems can enable a novice to perform at the level of an expert but must be developed and maintained very carefully.
– List the characteristics and basic components of expert systems.
– Outline and briefly explain the steps for developing an expert system.
– Identify the benefits associated with the use of expert systems.
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Principles and Learning Objectives
• Virtual reality systems have the potential to reshape the interface between people and information technology by offering new ways to communicate information creatively.
– Define the term virtual reality and provide three examples of
virtual reality applications.
• Special-purpose systems can help organizations and individuals achieve their goals.
– Discuss examples of special-purpose systems for organizational and individual use.