Artificial Intelligence, Expert Systems, and Virtual Reality Chapter 7

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

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.

Natural and Artificial Intelligence

Conceptual Model of AI www.robocup.org Handwriting recognition: http://members.aol.com/Trane64/java/JRec.html

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

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

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

Rules Whale Watcher demo JESS and the Sticks game Other demos http://www.aiinc.ca/demos/whale.html JESS and the Sticks game http://herzberg.ca.sandia.gov/jess/ Other demos http://www.cs.wisc.edu/~mariopi/AIDemos.html

Knowledge Acquisition Facility

Expert System Development Process

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

Expert Systems Development Alternatives

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.

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

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

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 http://www.media.mit.edu/wearables/mithril/

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

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

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