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2. Define artificial intelligence, and explain how AI technologies support decision making
Describe an expert system, its applications, and its components
Describe case-based reasoning
Summarize the types of intelligent agents and how they are used
Describe fuzzy logic and its uses

3. Explain artificial neural networks
Describe how genetic algorithms are used
Explain natural-language processing and its advantages and disadvantages
Summarize the advantages of integrating AI technologies into decision support systems
Explain contextual computing

4. 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

5. 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

6. 13.1 Applications of AI Technologies

7. Involve application of AI Excel at performing simple, repetitive tasks
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)

8. Use following programming languages
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

9. Advantages of robots over humans in the workplace
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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 13.1 An Expert System Configuration

16. Uses of Expert Systems Airline industry Forensics lab work
Banking and finance
Education
Food industry
Personnel management
Security
US Government
Agriculture

17. 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

18. 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

19. 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

20. 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

21. Offers a solution after searching for a match
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

22. Software capable of reasoning and following rule-based processes
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)

23. Characteristics of Intelligent Agents
Adaptability
Autonomy
Collaborative behavior
Humanlike interface
Mobility
Reactivity

24. 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

25. Categories of Available Intelligent Agents
Shopping and information
Personal
Data-mining
Monitoring and surveillance

26. 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

27. Perform specific tasks for a user
Personal Agents
Perform specific tasks for a user
Remembering information for filling out Web forms
Completing addresses after the first few characters are typed
Tasks performed by personal agent
Generate auto-response messages
Forward incoming messages
Create replies based on the content of incoming messages

28. Work with a data warehouse
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

29. Monitoring and Surveillance Agents
Track and report on computer equipment and network systems to predict when a system crash or failure might occur

30. 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

31. 13.3 Degree of Membership in a Fuzzy System

32. Areas Where Fuzzy Logic is Used
Search engines
Chip design
Database management systems
Software development

33. 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
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

34. 13.4 Artificial Neural Network Configuration

35. Tasks Involving the Use of ANNs
Bankruptcy prediction
Credit rating
Investment analysis
Oil and gas exploration
Target marketing

36. 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

37. 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

38. NLP Systems

39. 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

40. 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

41. 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)

42. 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

43. Achieved by using the information technologies
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

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

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

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

47. 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

48. 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