History of AI:
Important research that laid the groundwork for AI:
In 1931, Goedel layed the foundation of Theoretical Computer Science1920-30s: He published the first universal formal language and showed that math itself is either flawed or allows for unprovable but true statements.
In 1936, Turing reformulated Goedel’s result and church’s extension thereof. In 1956, John McCarthy coined the term "Artificial Intelligence" as the topic of the Dartmouth Conference, the first conference devoted to the subject.
In 1957, The General Problem Solver (GPS) demonstrated by Newell, Shaw & Simon
In 1958, John McCarthy (MIT) invented the Lisp language.
In 1959, Arthur Samuel (IBM) wrote the first game-playing program, for checkers, to achieve sufficient skill to challenge a world champion.
In 1963, Ivan Sutherland's MIT dissertation on Sketchpad introduced the idea of interactive graphics into computing.
In 1966, Ross Quillian (PhD dissertation, Carnegie Inst. of Technology; now CMU) demonstrated semantic nets
In 1967, Dendral program (Edward Feigenbaum, Joshua Lederberg, Bruce Buchanan, Georgia Sutherland at Stanford) demonstrated to interpret mass spectra on organic chemical compounds. First successful knowledge-based program for scientific reasoning.
In 1967, Doug Engelbart invented the mouse at SRI
In 1968, Marvin Minsky & Seymour Papert publish Perceptrons, demonstrating limits of simple neural nets.
In 1972, Prolog developed by Alain Colmerauer.
In Mid 80’s, Neural Networks become widely used with the Backpropagation algorithm (first described by Werbos in 1974).
1990, Major advances in all areas of AI, with significant demonstrations in machine learning, intelligent tutoring, case-based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games, and other topics.
In 1997, Deep Blue beats the World Chess Champion Kasparov
In 2002,iRobot, founded by researchers at the MIT Artificial Intelligence Lab, introduced Roomba,
a vacuum cleaning robot. By 2006, two million had been sold. Foundations of Artificial Intelligence:
Philosophy e.g., foundational issues (can a machine think?), issues of knowledge and believe, mutual knowledge, Psychology and Cognitive Science e.g., problem solving skills
Neuro-Science e.g., brain architecture
Computer Science And Engineering e.g., complexity theory, algorithms, logic and inference, programming languages, and system building.
Mathematics and Physics
e.g., statistical modeling, continuous mathematics,
Statistical Physics, and Complex Systems.
Application of AI:
AI algorithms have attracted close attention of researchers and have also been applied successfully to solve problems in engineering. Nevertheless, for large and complex problems, AI algorithms consume considerable computation time due to stochastic feature of the search approaches
1) Business; financial strategies2) Engineering: check design, offer suggestions to create new product, expert systems for all engineering problems
3) Manufacturing: assembly, inspection and maintenance
4) Medicine: monitoring, diagnosing
5) Education: in teaching
6) Fraud detection
7) Object identification
8) Information retrieval
9) Space shuttle scheduling