1.Soft ComputingLecture 06: Introduction “Genetic Algorithms are good at to Genetic Algorithmstaking large, potentially huge search spaces and navigating them,looking for…

Soft Computing Lecture 17 Introduction to probabilistic reasoning. Bayesian nets. Markov models Why probabilistic methods? Probabilistic is used for description of events…

Soft Computing Lecture 18 Foundations of genetic algorithms (GA). Using of GA. Genetic algorithm Using GA for learning of MLP For evolution of weights For evolution of structure…

Soft Computing Lecture 13 Reinforcement learning Examples of reinforcement learning A master chess player makes a move. The choice is informed both by planning--anticipating…

Soft Computing Lecture 14 Clustering and model ART Definition Clustering is the process of partitioning a set of objects into subsets based on some measure of similarity…

Soft Computing Lecture 4 Fuzzy logic, linguistic variables, pseudo-physical logics 8.3 Linguistic variable 8.3.1 Definition of linguistic variable When we consider a variable,…

Soft Computing Lecture 24 Future of soft computing. Introduction to generalized theory of uncertainty Directions of future development of soft computing Development of Generalized…

* * Intelligent Systems and Soft Computing Lecture 0 What is Soft Computing Intelligent Systems and Soft Computing * * Intelligent Systems and Soft Computing Soft computing…

Soft Computing Lecture 24 Future of soft computing. Introduction to generalized theory of uncertainty Directions of future development of soft computing Development of Generalized…

1/24/2008 * Intelligent Systems and Soft Computing Lecture 2 Introduction, or what is knowledge? Rules as a knowledge representation technique The main players in the development…