PPT-Chapter 5: Evolutionary Requirements

51 Definition Requirements Requirements are capabilities and conditions to which the system and more broadly the project must conform The UP does not attempt to fully define the requirements before programming but instead promotes a systematic approach to finding documenting . Read Chapter 4. Phylogeny. All living organisms are related to each other having descended from common ancestors.. Understanding the evolutionary relationships between groups enables us to reconstruct the tree of life and gain insight into history of evolutionary change.. Steven . M. . Roels. Department . of Zoology, Michigan State . University. Introduction. “. It follows that naturalistic evolution will not attract a majority of Americans until our nation becomes less religious.” – . Materialism. By Frank W. Elwell. Note:. This . presentation is based on the theories of Steven K. Sanderson. . as presented in his books listed in . the bibliography. . A more complete summary of . Some slides are imported from . “Getting creative with evolution” from. P. Bentley, University College London. http://evonet.dcs.napier.ac.uk/summerschool2002/tutorials.html. http://en.wikipedia.org/wiki/Evolutionary_art. Domestication. Pedro . Semōes. , . Josiane. Santos, Margarida Matos. Presentation by . Priya. Singha, UC, Irvine. Some questions for you to think about:. What is . domestication. ? How do different . Week 5. General feedback: Thought Paper #1. A thought paper is about . your . reasoned . thoughts. If 40% of your TP is your summary, you are losing ~40% of your marks. I do not grade introductions (but you still need them). 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. Multi-objective Evolutionary Optimization. 1. Sources. “Handbook of Natural Computing,” Editors . Grzegorz. Rosenberg, Thomas Back and . Joost. N. . Kok. , Springer 2014. . “Multi-Objective Evolutionary Algorithms”, . Objective. SWBAT explain and demonstrate that organisms share many conserved core processes and features that evolved and are widely distributed among organisms today.. Agenda. Chapter 25 Quiz. Chapter 26 notes: sections 26.1, 26.2, and 26.3. . Multiobjective. . Optimization. . Algorithms. Karthik. . Sindhya. , . PhD. Postdoctoral Researcher. Industrial Optimization Group. Department of Mathematical Information Technology. Karthik.sindhya@jyu.fi. A discussion of the field of . evolutionary psychology. The study of behavior and mental function. Goal is to understand behavior . Psychology. Studies how evolution has. generated the diversity . of living organisms. 1. Behavior Genetics and Evolutionary Psychology. Behavior Genetics: Predicting Individual Differences. Genes: Our Codes for Life. Twin and Adoption Studies . Temperament and Heredity. Nature . and. Nurture. What you will learn. Common traits of problems which can be solved by EAs efficiently. “HUMIES” competition with few examples of winning solutions of various problems. When EAs can be competitive with Reinforcement Learning techniques when solving various control problems. 1. 2. What are the evolutionary relationships between a human, a mushroom, and a flower?. A phylogeny based on DNA data reveals that animals (including humans) and fungi (including mushrooms) are more closely related to each other than .