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C SC 421: Artificial Intelligence

C SC 421: Artificial Intelligence …or Computational Intelligence Alex Thomo 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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C SC 421: Artificial Intelligence

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  1. C SC 421: Artificial Intelligence • …or Computational Intelligence Alex Thomo

  2. What is AI? • American Association for Artificial Intelligence: • "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

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