Darwin builds better cars
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Transcript of Darwin builds better cars
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Darwin builds better carsLessons evolving online vehicles
GK-12 2013Anne, Liz & Sara
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Evolution & Engineering• Introduce a program that incorporates
evolutionary and engineering principles to build cars best adapted to their track
• Designing vehicles is a great hook to get students thinking about adaptation and evolution
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You as an engineer:Create a car that is best
adapted to it’s environment
(a car’s “fitness” is dependent on how far it can travel in the environment)
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Evolution & Engineering• Introduce a program that incorporates
evolutionary and engineering principles to build cars best adapted to their track
• Designing vehicles is a great hook to get students thinking about adaptation and evolution
• Start with Lego cars to get them engaged• Move into working with online program
Testing convergent evolution and adaptation
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You as an engineer:build the best Lego car you can
YOU CAN USE:• Up to four wheels (0-4)• One platform (gray piece)• Up to four additional parts (0-4) (any other color)
Trial runs: the goal is to get your car to go as far as possible – write name and best time on the board
After everyone has their starter pieces, you can pick up more pieces (or remove them!) to engineer a faster car
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Integrating evolution and engineering:Using biological concepts to solve problems
wikimedia commons
Leonardo da Vinci
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Evolution as a process:How can we use principles from evolution
to improve our Lego cars?
• Variation• Selection• Inheritance• Time
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Evolution as a process:How can we use principles from evolution
to improve our Lego cars?
• Variation: the fuel for natural selection
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Evolution as a process:How can we use principles from evolution
to improve our Lego cars?
• Selection: acts on variation in a non-random way, leaving behind individuals with beneficial traits
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Evolution as a process:How can we use principles from evolution
to improve our Lego cars?
• Inheritance: individuals with beneficial traits will survive better and pass on more genes to future generations
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Evolution as a process:How can we use principles from evolution
to improve our Lego cars?
• Time: over many generations, the beneficial adaptations will spread through the population
Generation 1 Generation 2 Generation 3
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Evolution and Engineering: BoxCar2D• Computer program for vehicle evolution developed by
Ryan Weber• Virtual environment including the effects of gravity,
friction, collisions, motor torque, and spring tension• Each car represents an individual in a population• Each generation the cars move along a track, with
distance traveled considered their “fitness”• To produce the next generation, cars mate - their traits
recombine, and some mutation adds additional variation to produce offspring
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www.BoxCar2D.comOpen web browser and go to:
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Keep this round of evolution running in the background
Don’t close the window or open new tabs – only open new windows!!
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Observing evolution in BoxCar2D
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Evolution & Engineering:How does BoxCar2D use principles from evolution
to develop better performing cars?
• Variation• Inheritance• Selection• Time
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Evolution as a process:variation
Each car is represented by one chromosome, with 40 variables on each chromosome
All of the car’s traits are coded on the chromosome: how many wheels, angles, length, speed…
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• Where does the variation come from?• Initial variation from randomly-generated cars• Chromosomes undergo mutation at a user-set rate each
generation; mutated traits are marked by a color change
Evolution as a process:variation
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Each population contains 20 unique individuals
Evolution as a process:variation
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At the end of each generation, cars are paired up to “reproduce”
Cars that move the furthest get “mated” most often, so they contribute most to the next generation
Evolution as a process:selection
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A lot like meiosis…
Parent chromosomes “cross over” twice to produce offspring that are a mixture of traits
Evolution as a process:inheritance
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Generation 1 Generation 30 Generation 90
Evolution as a process:time
over many generations, adaptations will spread through the population; traits that work less well will dwindle
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• Keep the program running for many generations, and watch the cars evolve over time!
Evolution as a process:time
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• Variation• Inheritance• Selection• Time (generations)• Design??
Evolution as a process:
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BoxCar allows you to add design into your vehicles along the way
• How does this differ from evolution by natural selection?
• What are potential issues to address when using BoxCar to reinforce principles of evolution in your classroom?
vs.
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COPYING A CAR OUT OF THE POPULATION:-Click on the row in the table representing the car you want-Click “copy selected”-Paste into a new population on a new track, or back into the designer
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Evolution with hand-engineering in BoxCar2D(excerpted from boxcar2d.com/about.html)
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• Importing your designed car into the program:– In the Derp Bike Designer, click “copy to
clipboard”– Go to the main page, click “input seed/choose
terrain” – keep on the same track – Click in the box that pops up and hit control-V to
paste your car’s code– Click “input seed car” to start running
• Your car will show up first; the next ones in the population will be mixtures of your design and random cars
Evolution with hand-engineering in BoxCar2D(excerpted from boxcar2d.com/about.html)
INSTRUCTIONS WILL STAY ON THE SCREEN- DON’T COPY THEM DOWN!
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Testing local adaptationHYPOTHESIS AND PREDICTION• Local adaptation hypothesis: local genotypes perform better in their
own environment than foreign genotypes do (home team always beats away team)
• Prediction: BoxCar populations will move farther on the track they evolved on that on the track they didn’t evolve on.
METHODS• Record population mean fitness (estimate where black line crosses
y-axis)• Run the same population for one generation in the OTHER track,
then record mean fitness in this environment. CONCLUSION• Compare with person next to you – did your population do better
than theirs in your environment? Did theirs do better than yours on the track they evolved on?
• Raise hands – who found local adaptation? Who didn’t? Discuss!
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• Share some of the cars that are evolving
• Do different populations on the same track look similar? Would we expect them to?
• What traits (features of your successful cars) do you think might be adaptations to your track?
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Adaptation & Convergence• Independent evolution of a similar solution
to the same pressure – Different paths to solve the problem– May find the same solution or different
• In engineering, different ways to solve the same problem?
• Brainstorm – examples? (Engineering or biology)
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Diliff Whit Welles
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Diliff Whit Welles
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Extensions• Testing predictions about manipulating
population size and/or mutation rate• Tree thinking: building evolutionary trees, saving
code or images of cars at nodes as “fossils”• Local adaptation: in reciprocal transplants, do
cars evolved on track “A” do worse on track “B” than cars evolved on track “B”?
• Full-circle inquiry exercises– Students come up with their own questions– Emphasizing replication – Statistical testing – t-test or ANOVA using fitness
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Ryan WeberLouise MeadTom GettyMike WiserBjorn OstmanBEACON HS Institute students
Acknowledgements:
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eNqzfxySMo1Vbqf9z+ZNZoJaFvYrZ4LALAe2A6tOmD2ot3+mphD6/7a1/Rt5N+dpTU/s72gu3Xo/Pt/+n6zx9Q0xn+DqORjAwP4aU/eM5xGP7H+sXDij4rCX/Ytsq8cv59213wlRh64eCFgdGDnUStmUJtnf4YlqyTvTAjbnhsL8aKVdy+wPe1uGeEv/AAox2v92+Hcgu83F/qb9lSLVMj6gGIsDz9OcMrNVTvaPQ0IsZpf+/g8E9g++PdaMDu2w/wGxACz2MyJ6gm9HH8wdQGFm+28XHp36n8MEUwcWu/bXMTxRewZc3el//xiQAYh/+t9phtMzGBiAFAQDxfi5rRj+VTcyJM7jZtipKcHwhNuO4XKuClAHEwAUb5JX
Code for a cool car!