1. Artificial Intelligence, Expert Systems, and Virtual Reality
Chapter 7

2. Artificial Intelligence
People, procedures, hardware, software, data, and knowledge needed to develop computer systems and machines that demonstrate characteristics of intelligence
Test for AI
Unable to tell whether you are interacting with a computer or human

3. The Nature of Intelligence
Learn from experience & apply the knowledge
Handle complex situations
Solve problems when important information is missing
Determine what is important
React quickly and correctly to new situations
Understand visual images
Process and manipulate symbols
Be creative and imaginative
Use heuristics (rules of thumb)
Humans naturally learn from experience – that is, by trial and error. And humans can apply what they learn to different contexts. Neither trait comes naturally to AI systems – they can only learn and apply what they’ve been programmed to learn – and the programming is difficult. Humans can learn in multiple areas and automatically apply what they learn.
Humans are often involved in complex situations. In business, executives face complicated legislation, rapidly changing markets and competition, and many more complexities, yet must make decisions, sometimes quickly, that affect their company’s future. People can make mistakes and learn from them. However, computers can handle only those complex situations that they’re programmed to handle.
Humans continually make decisions under uncertainty – that is, with partial or even inaccurate, information. AI systems can handle such situations in many contexts.
Everyday humans receive masses of incoming information. People can screen the information and discard irrelevant information – a skill built through experience. Computers are limited by their programming – and it’s not easy to program a computer to know what’s irrelevant.

4. Natural and Artificial Intelligence

5. Conceptual Model of AI www.robocup.org Handwriting recognition:

6. Expert System Characteristics
Can explain their reasoning or suggested decisions
Can display “intelligent” behavior
Can draw conclusions from complex relationships
Can provide portable knowledge
Can deal with uncertainty

7. Expert System Limitations
Not widely used or tested
Difficult to use
Limited to relatively narrow problems
Cannot readily deal with “mixed” knowledge
Possibility of error
Cannot refine own knowledge base
Difficult to maintain
May have high development costs
Raise legal and ethical concerns

8. Components of an Expert System
Backward chaining
Forward chaining
Comparison of backward and forward chaining
Assembling human experts
The use of fuzzy logic
The use of rules
The use of cases

9. Rules Whale Watcher demo JESS and the Sticks game Other demos
JESS and the Sticks game
Other demos

10. Knowledge Acquisition Facility

11. Expert System Development Process

12. Participants in Expert System Development
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

13. Expert Systems Development Alternatives

14. When to Use Expert Systems
High payoff
Preserve scarce expertise
Distribute expertise
Provide more consistency than humans
Faster solutions than humans
Training expertise
Since expert systems can be difficult and expensive to develop, they should be used where they can be most beneficial. This slide summarizes situations where expert systems have been shown to be worth implementing.
Clearly, when there is a high potential payoff, or when the expertise is needed at a place dangerous to humans, it makes sense to develop the expert system.
It is generally also worthwhile to develop an expert system to capture and preserve expertise that not many people have, that is expensive, or that can’t be duplicated in other ways. Also, an expert system is called for when this kind of scarce expertise is needed in many locations at once.
No matter how hard they try, people cannot be 100% consistent – they tire, have bad moods, or are distracted. Where consistency is needed – say in loan approval – investing in an expert system may be worthwhile.
In complex tasks, such as configuring large computer installations, it may take humans too long to do the job for the company to be competitive. Using an expert system to complete the task quicker than your competition would be wise.
And finally, sharing scarce expertise or training others in the area, is a solid use of expert systems.

15. Applications of Expert System and Artificial Intelligence
Credit granting and loan analysis
Stock Picking
Catching cheats and terrorists
Budgeting
Information management and retrieval
Games
Virus detection
Hospitals and medical facilities

16. Virtual Reality
Binocular Omni-Orientation Monitor
(BOOM)
A system that enables one or more users to move and react in a computer-simulated environment
Head mounted display
Data glove
CAVE
Haptic interface, aka force feedback

17. Wearable computers / Augmented Reality
Computers worn as part of clothing, jewellery, etc.
Computers are always present
Context-aware: Senses where the user is, what is happening
MIT Media labs

18. VR Applications Medicine Education and training Entertainment
used to link stroke patients to physical therapists
Education and training
used by military for aircraft maintenance
Entertainment
CGI
The Matrix Reloaded, Star Wars, LOTR
Real Estate Marketing and Tourism
Used to increase real estate sales
Virtual reality tour of the White House

19. Other Specialized Systems
Segway Personal Transporter
Adaptive brain interface technology
Personal awareness assistant (PAA)

20. Coming up Thursday Tuesday Tutorial 8 Lab 7 due S&R Chapter 8
Database design due