1. 4
Intelligent Systems

2. Explain the potential value and the potential limitations of artificial intelligence.
Provide examples of the benefits, applications, and limitations of expert systems.
Provide examples of the use of neural networks.

3. Provide examples of the use of fuzzy logic.
Describe the situations in which genetic algorithms would be most useful.
Describe the use case for several major types of intelligent agents.

4. Introduction to Intelligent Systems
Expert Systems
Neural Networks
Fuzzy Logic
Genetic Algorithms
Intelligent Agents

5. Introduction to Intelligent Agents
TG 4.1
Introduction to Intelligent Agents
Artificial Intelligence (AI)
Behavior by a machine that, if performed by a human being, would be considered intelligent.
Turing Test
Artificial Intelligence versus Natural (Human) Intelligence

6. TG 4.2
Expert Systems
Four Activities Involved in the Transfer of Expertise Expert  Computer  User
The Components of Expert Systems
Applications, Benefits, and Limitations of Expert Systems

7. Four Activities Involved in the Transfer of Expertise Expert  Computer  User
Knowledge Acquisition
Knowledge Representation
Knowledge Inferencing
Knowledge Transfer

8. The Components of Expert Systems
Knowledge Base
Facts
Rules
Inference Engine

9. Applications, Benefits, and Limitations of Expert Systems
Expert Systems Are Especially Useful in the Following Categories
Benefits of Expert Systems
Difficulties of Using Expert Systems

10. Applications, Benefits, and Limitations of Expert Systems
Expert Systems Are Especially Useful in the Following Categories
Interpretation
Prediction
Diagnosis
Design
Planning
Monitoring
Debugging
Repair
Instruction
Control

11. Applications, Benefits, and Limitations of Expert Systems
Benefits of Expert Systems
Increased Output and Productivity
Increased Quality
Capture and Dissemination of Scarce Resources
Accessibility to Knowledge and Help Desks
Reliability
Ability to Work with Incomplete or Uncertain Information
Provision of Training
Enhancement of Decision-making and Problem-solving Capabilities
Decreased Decision-Making Time
Reduced Downtime
Difficulties of Using Expert Systems
Transferring domain expertise from human experts to the expert system can be difficult because people cannot always explain what they know
Even if the doman experts can explain their entire reasoning process, automating that process may not be possible
In some contexts, there is a potential liability from the use of expert systems.

12. Applications, Benefits, and Limitations of Expert Systems
Benefits of Expert Systems
Increased Output and Productivity
Increased Quality
Capture and Dissemination of Scarce Resources
Accessibility to Knowledge and Help Desks
Reliability
Ability to Work with Incomplete or Uncertain Information
Provision of Training
Enhancement of Decision-making and Problem-solving Capabilities
Decreased Decision-Making Time
Reduced Downtime

13. Applications, Benefits, and Limitations of Expert Systems
Difficulties of Using Expert Systems
Transferring domain expertise from human experts to the expert system can be difficult because people cannot always explain what they know
Even if the domain experts can explain their entire reasoning process, automating that process may not be possible
In some contexts, there is a potential liability from the use of expert systems.

14. TG 4.3
Neural Networks
A system of programs and data structures that simulates the underlying functions of the biological brain
Examples of the Use of Neural Networks
Bruce Nuclear Facility (Ontario, Canada)
Research into Diseases (Alzheimer’s, Parkinson’s, Epilepsy, etc.)
Banking System Fraud Detection

15. TG 4.4
Fuzzy Logic
A branch of mathematics that deals with uncertainties by simulating the processes of human reasoning.

16. TG 4.5
Genetic Algorithms
Mimics the evolutionary, “survival-of-the-fittest” process to generate increasingly better solutions to a problem.
Three Functional Characteristics of Genetic Algorithms
Examples of Genetic Algorithms in the Field

17. Three Functional Characteristics of Genetic Algorithms
Selection
Crossover
Mutation

18. Examples of Genetic Algorithms in the Field
Boeing’s Aircraft – Part Design
Marks and Spencer – Managing Inventories
Air Liquide – Optimal Production Schedules and Distribution Points in Supply Chain

19. TG 4.6
Intelligent Agents
A software program that assists, you, or acts on your behalf, in performing repetitive computer-related tasks.
Information Agents
Monitoring-and-Surveillance Agents
User Agents (or Personal Agents)