PPT-Meet the Evolutionary Pioneers

Researching evolution scientists WALT learn more about the work of A nning D arwin and W allace The LEARNING In todays Science lesson you will be researching 3 key scientists who played a key role in the development of evolutionary theory. Unit 4 Week 3 Day 3. Question of the Week:. What does it mean to be a pioneer?. Cause and Effect: Shows a relationship. . cause .  effect. Inferring: Using clues from the text and prior knowledge to form opinions. Social Studies . A is for Americans.. In the mid 1800s, America began to acquire land to the west of the Mississippi River. Americans believed they should have all of the land between the Atlantic and Pacific Oceans. Americans began traveling west in search of new lands and ”elbow room”. . vs.. poker games. Yikan. Chen (yc2r@virginia.edu). Weikeng. Qin (wq7yt@virginia.edu). 1. Outline. 2. Evolutionary Algorithm. Poker!. Artificial Neural Network. E-ANN. Evolutionary algorithm. 3. Evolutionary algorithm. 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. LDS Pioneer Trek. As will be mentioned in greater detail the Pioneer Trek is enacted as a remembrance of LDS ancestors who gave up so much for their current freedoms.. The pioneers were the first to believe upon their beliefs of a modern prophet and the Book of Mormon in connection with the Bible. As a result they were persecuted and kicked out of many towns, even those they personally settled.. The people in America’s history who traveled . west. to develop new areas and begin new towns and communities.. Much like the . Pilgrims. , the pioneers settled on territory that had not been occupied previously by foreign or European people. However, the territory may have been lived on by . 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. 1. Evolutionary Algorithms. CS 478 - Evolutionary Algorithms. 2. Evolutionary Computation/Algorithms. Genetic Algorithms. Simulate “natural” evolution of structures via selection and reproduction, based on performance (fitness). Evo. . Psyc. is the application of Darwinian principles to the understanding of human nature..  . To understand how Darwinian principles are applied to humans one must first understand a number of concepts and premises upon which . Evo. . Psyc. is the application of Darwinian principles to the understanding of human nature..  . To understand how Darwinian principles are applied to humans one must first understand a number of concepts and premises upon which . 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. SouthernIllinoiswasthefirstpartofIllinoistobesettledPioneersbuilttheirhomesnearriversandwoodsRiversprovidedeasytransportationTheforestsfurnishedbuildingmaterialsandfuelforheatingtheirhomesandcookingan Behaviours are evolved responses to the environment in which the human species evolved.. There are two levels on which behaviours can be transmitted:. Genetic. Cultural. Timing information can inform as to which level generates a particular behaviour.. 1. Evolutionary Algorithms. CS 472 - Evolutionary Algorithms. 2. Evolutionary Computation/Algorithms. Genetic Algorithms. Simulate “natural” evolution of structures via selection and reproduction, based on performance (fitness).