Summer Semester 2009/10
Summer Semester 2010/11
Summer Semester 2011/12
Summer Semester 2012/13
Fundamentals of artificial intelligence MAR2SO1004
Course content:
Intelligence, Artificial Intelligence - introduction. Weak AI vs. strong AI. Touring test. Methods of knowledge representation. Knowledge bases. Expert systems: organisation,methodology of projecting. Heuristics.Heuristics searching vs. classical searching. Reasoning. Prolog - programming in logic. Models and learning in neural networks. Optimilisation of neural network architecture. Classification.Genetic algorithms. Applications.
Learning outcomes:
Ability of chosing and appliying the proper method of artificial intelligence in selected problem.
(in Polish) Rodzaj przedmiotu
Course coordinators
Bibliography
a) basic references:
1. Hastie T., Tibshirani R., FriedmanR. The elements of statistical learning : data mining, inference, and prediction. New York Springer, 2009.
2. Duda R. O., Hart P. E., Stork D. G.. Pattern classification / New York : Wiley J., 2001.
b) supplementary references:
1. Kłopotek M., A. [et al.]: Recent advances in intelligent information systems. Warsaw : Institute of Computer Science Polish Academy of Sciences : Academic Publishing House Exit, 2009.
2. Świć A., Lipski J.:Automation and control in industry. Lublin : Wydaw. Politechniki Lubelskiej, 2008.