Intelligent Systems

1

• 4

• Intelligent Systems

2

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

3

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

4

1. Introduction to Intelligent Systems
2. Expert Systems
3. Neural Networks
4. Fuzzy Logic
5. Genetic Algorithms
6. Intelligent Agents

5

• 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

1. Knowledge Acquisition
2. Knowledge Representation
3. Knowledge Inferencing
4. 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 (Alzheimers, Parkinsons,
  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

• Boeings 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)