C SC 421: Artificial Intelligence

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C SC 421 Artificial Intelligence

• or Computational Intelligence

Alex Thomo thomo_at_cs.uvic.ca
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What is AI?

• American Association for Artificial Intelligence
  
• "the scientific understanding of the mechanisms
  underlying thought and intelligent behavior and
  their embodiment in machines."

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What is AI? Differently said

• . . . Exactly what the computer provides is the
  ability not to be rigid and unthinking but,
  rather, to behave conditionally. That is what it
  means to apply knowledge to action It means to
  let the action taken reflect knowledge of the
  situation. . .
• -Allen Newell

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AI History

• In late 1955, Newell and Simon developed The
  Logic Theorist, considered by many to be the
  first AI program.
• The program, representing each problem as a tree
  model, would attempt to solve it by selecting the
  branch that would most likely result in the
  correct conclusion.

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AI History

• In 1956 John McCarthy regarded as the father of
  AI, organized a conference to draw the talent and
  expertise of others interested in machine
  intelligence for a month of brainstorming.
• He invited them to Vermont for "The Dartmouth
  summer research project on artificial
  intelligence."
• From that point on, because of McCarthy, the
  field would be known as Artificial Intelligence.

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AI History

• In the seven years after the conference, AI began
  to pick up momentum.
• Centers for AI research began forming at Carnegie
  Mellon and MIT.
• New challenges were faced further research was
  placed upon creating systems that could
  efficiently solve problems.
• And second, making systems that could learn by
  themselves.

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SHRLDU has just completed the command Find a
block which is taller than the one you are
holding and put on the box Example of microworld.
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AI History

• The first difficulty was the intractability of
  many of the problems that AI was attempting to
  solve.
• Most of the early AI programs solved problems by
  trying out different combinations of steps until
  a solution was found.
• This strategy worked out initially because
  microworlds contained very few objects.
• It was widely thought that scaling up was
  simply a matter of faster hardware.
• Well, not quite a lot of research was done to
  limit search.

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AI History

• Another advancement in the 1970's was the advent
  of the expert system. Expert systems predict the
  probability of a solution under set conditions.
• The applications in the market place were
  extensive, and over the course of ten years,
  expert systems had been introduced
• to forecast the stock market,
• aiding doctors with the ability to diagnose
  disease, and
• instruct miners to promising mineral locations.

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AI Industry

• During the 1980's AI was moving at a faster pace,
  and further into the corporate sector.
• General Motors, and Boeing relied heavily on
  expert systems.
• To keep up with the demand for the computer
  experts, companies such as Teknowledge and
  Intellicorp specializing in creating software to
  aid in producing expert systems formed.

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AI application in other fields of CS

• Databases
• Query processing the promise (not yet fully
  achieved) that the user can give any query and
  the DB query processor will re-express it into an
  optimal one.
• Data mining An information extraction activity
  whose goal is to discover hidden facts contained
  in databases.
• Using a combination of machine learning,
  statistical analysis, modeling techniques and
  database technology, data mining finds patterns
  and subtle relationships in data and infers rules
  that allow the prediction of future results.
• Typical applications include market segmentation,
  customer profiling, fraud detection, evaluation
  of retail promotions, and credit risk analysis.
• Web computing
• Software robots which search for different things
  in the Web.

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Topics

• The course covers three major topics
• Search
• Tree/Graph search
• Constraint Satisfaction
• Games
• Knowledge Representation Inference
• Propositional First Order Logic
• Rule-based systems
• Natural Language
• Machine Learning
• Nearest Neighbors
• Decision Trees
• Neural Networks
• SVM