Introduction to Evolutionary Computation Temi avanzati di Intelligenza Artificiale - Lecture 1 Prof....

Introduction to Evolutionary Computation Temi avanzati di Intelligenza Artificiale - Lecture 1

Prof. Vincenzo Cutello

Department of Mathematics and Computer Science University of Catania

Introduction to Evolutionary Computation - Lecture 1

2

Evolution

What is Evolution ?

Introduction to Evolutionary Computation - Lecture 1

3

"Disclaimer"

You may whish to treat this as an abstract idea only

It does not matter (in the context of Evolutionary Computation) !

Introduction to Evolutionary Computation - Lecture 1

4

Darwinian Evolution Four Postulates

1. Individuals within species are variable

2. Some of the variations are passed on to offspring

3. In every generation, more offspring are produced than can survive

4. The survival and reproduction of individuals are not random: The individuals who survive and go on to reproduce, or who reproduce the most, are those with the most favourable variations. They are naturally selected.

On the Origin of Species by Means of Natural Selection (Darwin 1859)

Introduction to Evolutionary Computation - Lecture 1

5

Nature of Natural Selection Based on "Evolutionary Analysis (Freeman & Herron, 2001)"

Natural Evolution acts... On Individuals, but the Consequences occur in the population On Individuals, not groups On Phenotypes, but evolution consist of changes in the Genotype On exixting traits, but can produce new traits

Evolution... Is backward looking Is not perfect Is nonrandom Is not progressive

Introduction to Evolutionary Computation - Lecture 1

6

Why are we Interested ? 'Results' of Evolution are

'Creative', 'Surprising', 'Unexpected' 'Highly adapted' to 'Environmental Niches'

God or Evolution ?

Can a program 'create things like this' ?

Introduction to Evolutionary Computation - Lecture 1

7

Why are we interested (contd..) ? Unsupervised ! No 'conscious' design No knowledge involved Instead: Reproductive Fitness But ! Natural Evolution had an extremely long time (3.7

Billion Years!) Natural Evolution acts in parallel

Introduction to Evolutionary Computation - Lecture 1

8

Evolutionary Algorithms Algorithms that are inspired by natural evolution Four Main Elements:

Group of Individuals - Population Source of Variation - Genetic Operators Reproductive Fitness - Fitness Survival of the Fittest - Selection

Search Process Trial and Error Recipe for chosing next trial

Introduction to Evolutionary Computation - Lecture 1

9

EA Examples 1: Optimization Airfoil Optimization

Other Examples Scheduling Function Optimization Chemical Process Optimization

Introduction to Evolutionary Computation - Lecture 1

10

EA Examples 2: Exploration Evolutionary Art

Other Examples Electronic Hardware Design Robot Control

Introduction to Evolutionary Computation - Lecture 1

11

Sex !

Skippers mating, from www.chaparraltree.com/ mn/insects.shtml

Introduction to Evolutionary Computation - Lecture 1

12

Some Terms from Genetics DNA

Very large linear self-replicating molecules found in all living cells, the physical carrier of Genetic Information (Deoxyribonucleic Acid)

Chromosome A single, very long molecule of DNA

Gene The basic unit of inheritance, (...) a length of DNA which exerts its

influence on an organisms form and function by encoding and directing the synthesis of a protein (...)

Allele One of a number of alternative forms of a gene that can occupy a

given genetic locus on a chromosome.

Introduction to Evolutionary Computation - Lecture 1

13

Mutation as a Source of Variation Mitosis: Nuclear division in Cells

Mutations: Errors during Mitosis Point Mutations: simple copy errors - create new alleles Duplication: duplicate stretch of DNA - creates extra genetic material others...

Most Mutations are Neutral !

Introduction to Evolutionary Computation - Lecture 1

14

Sexual Reproduction Additional Steps - Meiosis

Combination of chromosome sets from both parents Additional Division

Introduction to Evolutionary Computation - Lecture 1

15

Recombination in Sexual Reproduction

Mixing of genetic material Mixing chromosomes Mixing genes on single chromosomes (crossover) Creates new combination of existing alleles

This is why... ...you can inherit your mother's eyes, and your father's nose

Sexual Reproduction Can combine beneficial mutations that arise in different individuals Can elimiate disadvantageous mutations quickly

Introduction to Evolutionary Computation - Lecture 1

16

Other Aspects of Natural Evolution in EC Punctuated Equilibrium Viruses Co-Evolution Genetic Engineering Non-Mendelian Inheritance Dominant and Recessive Genes

Introduction to Evolutionary Computation - Lecture 1

17

Course Overview Part 1: Basics

Representations, Selection, Search Operators

Part 2: Other Issues Niching, Co-Evolution, Constraint Handling, Multi-

Objective Problems, ...

Part 3: Theory Background Knowledge, Basic Results

Throughout: Tutorials Tutorials, Exercices, Demos

Introduction to Evolutionary Computation - Lecture 1

18

References and Resouces for this Lecture Books

Hartl, Daniel L. Essential Genetics Jones and Bartlett Publishers, 1996. Introductory genetics text (Barnes Library, q QH 430) (Advanced)

Freeman, Scott and Herron, Jon. C. Evolutionary Analysis 2nd edition, Prentice-Hall 2001. Good book on evolution. (Barnes Library, QH366.2) (Advanced)

Stearns, Steven C and Hoekstra, Rolf. F. Evolution. An Introduction Oxford University Press, 2000. (Barnes Library, QH366.2) (Advanced)

Lawrence, Eleanor Henderson's Dictionary of Biological Terms 10th edn. Longman Scientific and Technical, 1989. For Definitions

Web Resources Introduction to evolutionary Biology (Basic)

http://www.talkorigins.org/faqs/faq-intro-to-biology.html An Introduction to Genetic Analysis Online Book (Advanced)

http://www.ncbi.nlm.nih.gov/books/bv.fcgi?call=bv.View..ShowTOC&rid=iga.TOC