Machine Intelligence - Lecture 19 (Opposition-Based Learning, GAs, DE)

SYDE 522 – Machine Intelligence (Winter 2019, University of Waterloo) Target Audience: Senior Undergraduate Engineering Students Instructor: Professor H.R.Tizhoosh (http://kimia.uwaterloo.ca/) Course Outline - The objective of this course is to introduce the students to the main concepts of machine intelligence as parts of a broader framework of “artificial intelligence”. An overview of different learning, inference and optimization schemes will be provided, including Principal Component Analysis, Support Vector Machines, Self-Organizing Maps, Decision Trees, Backpropagation Networks, Autoencoders, Convolutional Networks, Fuzzy Inferencing, Bayesian Inferencing, Evolutionary algorithms, and Ant Colonies. Lecture 19 - Opposition-Based Learning, Differential Evolution, Genetic Algorithms Fitness