We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byJason Lane
Modified over 4 years ago
Exercise 1 Francesco Abate Niccolo` Battezzati Miguel Kaouk Apprendimento mimetico
EP – Program Flow Generate first population Generate new population by mutation Selection by tournament Goal? Max iterations? END μ μ q q σ, c.MAX_ITER μ + μ YES NO Fitness evaluation
EP – Program Architecture ep.conf EvoConfigParser EvoConfigurator main EvoAgent ( float x[D] ) float evaluate_fitness(float (*fitnessFnc)(EvoAgent *)) bool termination(bool (*terminationFnc)(EvoAgent *))
Experimental results μ q mean # of fitness evaluations σ = 0.8σ = 1.0σ = 2.5 10 n.s.237946379698 100 10n.s.227399560768 50n.s.2088101712028 D = 2, static σ
Experimental results μ mean # of fitness evaluations q = 10q = 50 103050/ 1001863330033 10006166656000 D = 2, dynamic σ
Experimental results μ mean # of fitness evaluations mean # of generations q = 10q = 50 10508475084// 10026431026423109203109 10002008700200816612001661 D = 5, dynamic σ
Experimental results μ mean # of fitness evaluations q = 10q = 50 10140058/ 100851783823050 100055675006165000 D = 10, dynamic σ
What type of data can a variable hold?
Foundations of Inferential Statistics: z-Scores. Has Anyone Else Been Bored to Tears by Descriptive Statistics? Descriptives are very important Descriptives.
Genetic Algorithms in Problem Solving EVOLVING COMPUTER PROGRAMS (1) t Evolving Lisp Programs Keplers Third Law: P 2 = cA 3 PROGRAM ORBITAL_PERIORD.
Section 7.2. Mean of a probability distribution is the long- run average outcome, µ, or µ x. Also called the expected value of x, or E(X). µ x = x i P.
Challenge 2 L. LaRosa for T. Trimpe 2008
Generative Design in Civil Engineering Using Cellular Automata Rafal Kicinger June 16, 2006.
Computing in Archaeology
How Big Should Sample Size be? Example We have data y=(y 1,…,y N ), where y~N(μ,σ 2 ) We want to test H 0 : μ=θ vs H 1 : μ θ –Chosen significance level=α=0.01.
Place Value Ones, Tens, and Hundreds.
Causes of Evolution Ruedi Nager Campbell et al. Chapter 23.
An Investigation on FPGA Placement Using Mixed Genetic Algorithm with Simulated Annealing Meng Yang Napier University Edinburgh, UK.
Chapter 7 Sampling Distributions
Interactive Evolutionary Computation Review of Applications Praminda Caleb-Solly Intelligent Computer Systems Centre University of the West of England.
Dependency Test in Loops By Amala Gandhi. Data Dependence Three types of data dependence: 1. Flow (True) dependence : read-after-write int a, b, c; a.
Normal distribution Learn about the properties of a normal distribution Solve problems using tables of the normal distribution Meet some other examples.
Huiswerkoplossings. 1) As x = -1 dan is y = -2(-1) – 8 = 2 – 8 = -6 As x = -2 dan is y = -2(-2) – 8 = 4 – 8 = -4 As x = -3 dan is y = -2(-3) – 8 = 6.
COURSE: JUST 3900 TIPS FOR APLIA Developed By: Ethan Cooper (Lead Tutor) John Lohman Michael Mattocks Aubrey Urwick Chapter 5: z-Scores.
COURSE: JUST 3900 TIPS FOR APLIA Chapter 7:
WHEEL OF EOC CLICK THE SPINNER BANKRUPT $50 $5 $10 $20 $500 $100.
© 2018 SlidePlayer.com Inc. All rights reserved.