Genetic Algorithms Chapter 9, Complexity: A Guided Tour

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<p>Genetic Algorithms and Nano-computing</p> <p>0</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 0Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 1Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 2Score: 50</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 2Score: 5Evolution by Natural Selection</p> <p>Charles DarwinOrganisms inherit traits from parents</p> <p>Traits are inherited with some variation, via mutation and sexual recombination</p> <p>Due to competition for limited resources, the organisms best adapted to the environment tend to produce the most offspring. </p> <p>Evolution by Natural Selection</p> <p>Charles DarwinOrganisms inherit traits from parents</p> <p>Traits are inherited with some variation, via mutation and sexual recombination</p> <p>Due to competition for limited resources, the organisms best adapted to the environment tend to produce the most offspring. </p> <p>This way traits producing adapted individuals spread in the population</p> <p>Evolution by Natural Selection</p> <p>Organisms inherit traits from parents</p> <p>Traits are inherited with some variation, via mutation and sexual recombination</p> <p>Due to competition for limited resources, the organisms best adapted to the environment tend to produce the most offspring. </p> <p>This way traits producing adapted individuals spread in the population</p> <p>in computersComputer(e.g., programs)</p> <p>Charles DarwinEvolution by Natural Selection</p> <p>Organisms inherit traits from parents</p> <p>Traits are inherited with some variation, via mutation and sexual recombination</p> <p>Due to competition for limited resources, the organisms best adapted to the environment tend to produce the most offspring. </p> <p>This way traits producing adapted individuals spread in the population</p> <p>in computersComputer(e.g., programs)</p> <p>Charles Darwin</p> <p>John Holland0</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 0Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 1Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 2Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 3Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 0Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 1Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 2Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 3Score: 100</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 4Score: 100</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 5Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 6Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 7Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 8Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 9Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 10Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 11Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 12Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 13Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 14Score: 300</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 15Score: 300</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 16Score: 400</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 17Score: 400</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 18Score: 500</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 19Score: 500</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 20Score: 600</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 0Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 1Score: 00</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 2Score: 100</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 3Score: 100</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 4Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 5Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 6Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 7Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 8Score: 200</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 9Score: 300</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 10Score: 300</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 11Score: 400</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 12Score: 400</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 13Score: 500</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 14Score: 500</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 15Score: 600</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 16Score: 60Generation 10Best average score = 0Generation 200Fitness = 240Generation 1000Fitness = 4920</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 17Score: 700</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Time: 18Score: 70Why Did The GAs Strategy Outperform Mine?My Strategy0</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9The GAs Evolved Strategy0</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 90</p> <p>1</p> <p>2</p> <p>3</p> <p>4</p> <p>5</p> <p>6</p> <p>7</p> <p>8</p> <p>9 0 1 2 3 4 5 6 7 8 9Principles of Evolution Seen in Genetic AlgorithmsPrinciples of Evolution Seen in Genetic AlgorithmsNatural selection works!</p> <p>Principles of Evolution Seen in Genetic AlgorithmsNatural selection works!</p> <p>Evolution proceeds via periods of stasis punctuated by periods of rapid innovation</p> <p>Principles of Evolution Seen in Genetic AlgorithmsNatural selection works!</p> <p>Evolution proceeds via periods of stasis punctuated by periods of rapid innovation</p> <p>Best fitness in populationGeneration numberPrinciples of Evolution Seen in Genetic AlgorithmsNatural selection works!</p> <p>Evolution proceeds via periods of stasis punctuated by periods of rapid innovation</p> <p>Exaptation is common</p> <p>Principles of Evolution Seen in Genetic AlgorithmsNatural selection works!</p> <p>Evolution proceeds via periods of stasis punctuated by periods of rapid innovation</p> <p>Exaptation is common</p> <p>Co-evolution speeds up innovationPrinciples of Evolution Seen in Genetic AlgorithmsNatural selection works!</p> <p>Evolution proceeds via periods of stasis punctuated by periods of rapid innovation</p> <p>Exaptation is common</p> <p>Co-evolution speeds up innovation</p> <p>Dynamics and results of evolution are unpredictable and hard to analyze</p>