Virtual Reality and Expert systems

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Virtual Reality andExpert systems
What are they? Where they are used? What is
their benefit to us?

• What are they?
• Where they are used?
• What is their benefit to us?

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Overview of ES/AI

• Origins pre WW2, symbolic logical problems,
  solving non-numeric problems.
• Impact structured narrowly defined problems,
  narrow, in-depth expertise.
• Pay-offs better solutions to logical problems,
  broader knowledge base.
• Relevance to organization structured logical
  problems solved.
• AI vs. ES

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What is intelligence?

• Learn from experience apply the knowledge
• Analyze, manipulate and solve complex situations
• Solve problems in information sparse environments
• Determine what is important, be able to prioritize

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What is intelligence (contd)?

• React quickly correctly to new situations
• Understand visual images
• Interpret, process manipulate symbols
• Be logical
• Be creative imaginative
• Recognize, establish/express, and use heuristics

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Comparison of natural and artificial intelligence
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Language of AI

• LISP
• The first programming language still going
  strong
• Prolog
• Used in many diagnostic systems today.

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The Major Branches of Artificial Intelligence

• Vision systems
• Pattern recognition
• Learning systems
• Computers that learn how to process better
• Natural language processing (speech recognition)
• Neural networks
• Computers functioning like human brain
• Find relationships, trends, patterns in data
• Complex problem solving in data-sparse
  environment
• Massively parallel processing
• Robotics
• Computer controlled machines with programmed
  intelligence (R2D2, HAL?).

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What can Expert Systems do?

• capture knowledge
• explain reasoning
• provide portable knowledge
• display intelligent behavior
• draw conclusions from complex relationships
• deal with uncertainty
• R2D2, HAL?

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Examples of ES applications

• Deliver Time-Saving Situation-Specific Answers
• Solve Troubleshooting, Tech Support and
  Diagnostics Problems (E.G. car, aircraft, medical
  etc. diagnostics)
• Attain and Maintain Regulatory and Policy
  Compliance
• Automate Routine Tasks
• Free Your Best People to be Even Better
• Keep Expertise from Getting Away
• Reach Problem-Solving Consensus and Consistency
• Bring Knowledge Assets and Interaction to Your
  Web Site

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ES examples

• Plant identification
• Credit scoring
• Political voting patterns
• For sample software and XML codes see
  http//www.scientio.com/onlinedemo.aspx
• For data and text mining applications and
  developments of data and rule base see
• http//www.scientio.com/developers.aspx
• Product Configuration
• Pricing Sales/Manufacturing

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ES examples (contd)

• Medical ES
• Example of medical diagnosis system
• http//www.easydiagnosis.com/modules.html

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ES examples (contd)

• Agricultural ES
• http//www.claes.sci.eg/Home/wes.htm
• Cell phone selection (view an explanation
  facility)
• http//www.vanguardsw.com/decisionscript/jupiter
  /default.htm
• Survey building and operating (see sample
  report)
• http//www.vanguardsw.com/vista/default.htm
• Also see (on Vanguard site)
• Retirement portfolios
• Web survey and analysis tools
• Federal Tax filing
• Other ES
• http//www.vanguardsw.com/decisionscript/Example
  s.htm

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Components of ESs
Components of Expert Systems
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Example of rules in the knowledge base

• Accepting payment in a store
• IF valid store ID
• THEN
• Allow purchase 25
• ELSE
• IF purchase gt 20
• THEN
• Call store manager
• ELSE
• IF two other ID's
• THEN
• Allow amount of purchase
• ELSE
• Call store manager
• END IF
• END IF
• END IF

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How do we acquire knowledge?
Knowledge acquisition is a process done with the
help of an AI analyst using a structured
procedure. Can you acquire the knowledge of
several human experts in the same knowledge base?
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Overview of virtual reality systems

• Origins late 1980s, solving 3-dimensional
  visualization problems in a dynamic virtual
  environment,
• Impact visual problem solving where
  visualization is necessary,
• Pay-offs better solutions to visual problems,
• Relevance to organization structured, complex
  design problems.

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Examples of VR systems

• Architectural displays
• Manufacturing simulation
• Ship building
• Environmental impact analysis
• Crime scene reconstruction
• Accident investigation
• Hazard detection
• Archeology
• Virtual reality examples see U of M site
• http//www-vrl.umich.edu/projects.html
• Equipment needed - VR products
• http//www.vrealities.com/main.html

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End Virtual Reality andExpert Systems(check out
the links!)