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Intelligent Control Methods Lecture 2: Artificial Intelligence Slovak University of Technology Faculty of Material Science and Technology in Trnava.

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Presentation on theme: "Intelligent Control Methods Lecture 2: Artificial Intelligence Slovak University of Technology Faculty of Material Science and Technology in Trnava."— Presentation transcript:

1 Intelligent Control Methods Lecture 2: Artificial Intelligence Slovak University of Technology Faculty of Material Science and Technology in Trnava

2 2 Concept „Artificial Intelligence“ A competence of machines to think A science branch 1950: Turing: Computing Machinery and Intelligence: „Can machines think?“

3 3 Intelligence: A competence to respond to new situation threw an activity correction.  A bee?  An adaptive controller? Vague answers and definitions. „Intelligence“ and „thinking“ are philosophical (not technical) categories.

4 4 Intelligence (a technical point of view): A complex of technical and program tools, techniques and methods for creation of systems, which are able to master tasks, which need „natural“ intelligence. Analogy: Bird´s and man´s flying Machines do not (and never will) think like a man (determined with a society and with his material, physical, intellectual and emotional needs), but they can simulate the external manifestations of thinking by their own tools.

5 5 History of AI: Classical period (1950 – 1965)  Declarative knowledge representation  Problem solution methods: theorem proving, graph searching Romantic period (1965 – 1975)  Universal problem solvers  Special program languages Modern period (1975 – 1985)  Review of tools and methods  Methods combination Period of expert systems (1985 – 1995)  Expert systems Period of AI integration into information technologies (1995 -...)

6 6 Problem core of AI: Information recognition, analysis and interpretation  Written, spoken, acoustic, graphical, tactile,... Knowledge representation  Knowledge formalization into the form, in which they can be effective stored and manipulated Problems solution (inference) Problems of man-machine communication, robotics, expert systems, machine learning, neuronal nets, genetic algorithms... )

7 7 Technical system is intelligent, if it: Perceives the environment  and understands, what is important Predicts the environment handling  Often without the environment model Uses obtained information for problem solution Plans the solution implementation Communicates with another intelligent systems (human or technical) Learns  From experiences  From generalization Adapts its behavior

8 8 AI perspectives: n Methods, techniques and tools of AI are integrated into another ICT  (pattern and speech recognition,...) The quality of AI system depends primarily on used knowledge (and only secondarily on knowledge manipulation mechanisms)  Direction at specialized knowledge acquisition, representation and exploitation.


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