PPT-Evolutionary Computation for Creativity and Intelligence

By Lauren Gillespie Gabby Gonzalez and Alex Rollins Neural Networks Brains Nodes Neurons Links Synapses Genotype Phenotype Evolutionary Algorithm A bstraction of evolution Asexual reproduction mutation. 13 NO 2 APRIL 2009 Multiobjective Optimization Problems With Complicated Pareto Sets MOEAD and NSGAII Hui Li and Qingfu Zhang Senior Member IEEE Abstract Partly due to lack of test problems the impact of the Pareto set PS shapes on the performance 6 NO 2 APRIL 2002 A Fast and Elitist Multiobjective Genetic Algorithm NSGAII Kalyanmoy Deb Associate Member IEEE Amrit Pratap Sameer Agarwal and T Meyarivan Abstract Multiobjective evolutionary algorithms EAs that use nondominated sorting and shar Dr. Frank McCown. Intro to Web Science. Harding University. This work is licensed under a . Creative Commons Attribution-. NonCommercial. -. ShareAlike. 3.0 . Unported. License. What is Collective Intelligence?. Group Administered Tests. Army . Alpha – 1917 - verbal. Army . Beta – 1917 - nonverbal. Army test image. Non Verbal Tests of Intelligence. Comprehensive Test of Nonverbal Intelligence (. CTONI-2). Group Administered Tests. Army . Alpha – 1917 - verbal. Army . Beta – 1917 - nonverbal. Army test image. Non Verbal Tests of Intelligence. Comprehensive Test of Nonverbal Intelligence (. CTONI-2). Khaled Rasheed. Computer Science Dept.. University of Georgia. http://www.cs.uga.edu/~khaled. Genetic algorithms. Parallel genetic algorithms. Genetic programming. Evolution strategies. Classifier systems. A. lgorithms. Andrew . Cannon. Yuki Osada. Angeline Honggowarsito. Contents. What are Evolutionary Algorithms (EAs. )?. Why are EAs Important?. Categories of EAs. Mutation. Self . Adaptation. Recombination. Week 4 NJ Kang, Creativity. What is that creative individuals do?. Sensing creative problems. . Sensing problems or difficulties. Making guesses or hypotheses about the problems. Evaluating the hypotheses, and possibly revising them. First lecture: Introduction to Evolutionary Computation. Second lecture: Genetic Programming. Inverted CERN School of Computing 2017. Daniel Lanza - CERN. Agenda. Genetic Programming. Introduction . to . Movies… anyone?. What should I do?. Tell me SOMETHING. Being more formal. Artificial Intelligence is something which gives computers the ability to learn without. b. eing explicitly programmed. Current state of machine intelligence. What is Intelligence?. . Mental quality consisting of the ability to learn from experie. nc. e, solve problems, and use knowledge to adapt. . Intelligence. Intelligence was thought as a thing, but it is an intangible concept.. First lecture: Introduction to Evolutionary Computation. Second lecture: Genetic Programming. Inverted CERN School of Computing . 2017. Daniel Lanza - CERN. Agenda. Introduction to Evolutionary Computati. 22 Pedagogical Hints1.To introduce the topic, teacher caninitiate discussion on psychologicalconstructs such as intelligence,personality, aptitude, values, etc.This would serve to point out thedifficu Edwin Creely. Monash University.  . Danah Henriksen. Arizona State University.  . Michael Henderson. Monash University. Text 1. When love is lost, it seems so bleak. A lonely heart, a voice too weak.