Hands-on Activity: Competing Evolved and Engineered Digital Organisms

Contributed by: Bio-Inspired Technology and Systems (BITS) RET, College of Engineering, Michigan State University

A man holds and examines a small model of a sleek silver airplane.
Engineers use evolutionary computation to optimize the wing design of supersonic aircraft.
copyright
Copyright © NASA/Michelle M. Murphy http://www.nasa.gov/topics/aeronautics/features/supersonic.html

Summary

Students engineer and evolve digital organisms with the challenge to produce organisms with the highest fitness values in a particular environment. They do this through use of the free Avida-ED digital evolution software application. The resulting organisms compete against each other in the same environment and students learn the benefits of applying the principles of natural selection to solve engineering design problems.
This engineering curriculum meets Next Generation Science Standards (NGSS).

Engineering Connection

Engineers apply their understanding of scientific and math principles to design and create devices, structures, materials and processes. Typically, engineers identify a problem, brainstorm possible solutions, and then create and test prototypes to find the best solution. Engineers often use computer modeling for this type of optimization. Evolutionary computation applies the principles of evolution by natural selection to identify the best potential solutions and often suggests possible solutions that engineers would not have ever considered.

Pre-Req Knowledge

A basic understanding of natural selection and the engineering design process is helpful.

Learning Objectives

After this activity, students should be able to:

  • Explain how the principles of natural selection can be applied to solve engineering design problems.
  • Compare and contrast the process of natural selection and the engineering design process.

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Educational Standards

Each TeachEngineering lesson or activity is correlated to one or more K-12 science, technology, engineering or math (STEM) educational standards.

All 100,000+ K-12 STEM standards covered in TeachEngineering are collected, maintained and packaged by the Achievement Standards Network (ASN), a project of D2L (www.achievementstandards.org).

In the ASN, standards are hierarchically structured: first by source; e.g., by state; within source by type; e.g., science or mathematics; within type by subtype, then by grade, etc.

  • Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem. (Grades 9 - 12) Details... View more aligned curriculum... Do you agree with this alignment?
  • Communicate scientific information that common ancestry and biological evolution are supported by multiple lines of empirical evidence. (Grades 9 - 12) Details... View more aligned curriculum... Do you agree with this alignment?
  • Inventions and innovations are the results of specific, goal-directed research. (Grades 9 - 12) Details... View more aligned curriculum... Do you agree with this alignment?
  • Species evolve over time. Evolution is the consequence of the interactions of (1) the potential for a species to increase its numbers, (2) the genetic variability of offspring due to mutation and recombination of genes, (3) a finite supply of the resources required for life, and (4) the ensuing selection by the environment of those offspring better able to survive and leave offspring. (Grades 9 - 12) Details... View more aligned curriculum... Do you agree with this alignment?
Suggest an alignment not listed above

Materials List

Each group needs:

For the teacher:

  • flash drive or email access to obtain groups' text files of highest fitness organisms
  • computer connected to a projector (for the competition, operated by the instructor)

Introduction/Motivation

(Review the associated Introduction to Evolutionary Computation lesson with students. They should have already been introduced to the Avida-ED software. You may wish to show the tutorial video again or allow some time for students to familiarize themselves with the program if they have not used it before. Have students be prepared with paper and pencil for taking notes during the Introduction/Motivation section, as described in the Assessment section.)

Drawing shows a futuristic green supersonic jet flying fast and high above the clouds.
Figure 1. Concept design for a supersonic aircraft that drastically lowers the level of sonic booms. Evolutionary computation methods are used to optimize the wing design of supersonic aircraft.
copyright
Copyright © NASA/Lockheed Martin http://www.nasa.gov/multimedia/imagegallery/image_feature_2025.html

How do engineers determine the optimum designs for supersonic aircraft? (Listen to student answers.) Engineers apply their knowledge of scientific and mathematical principles and brainstorm all sorts of possible design solutions. They often use computer modeling to help determine the most effective designs. Then they create and test prototypes in a continuing cycle to optimize the design.

As an example, evolutionary computation methods are applied to optimize the wing design of supersonic aircraft. (Show students the Figure 1 image of a supersonic aircraft design.) This drawing shows the concept for a supersonic aircraft design that drastically lowers the level of sonic booms. This design is intended to reduce the sonic shockwave signature so it barely registers on buildings and people below, and reduce drag.

How is the optimum design of aircraft similar to an adaptation of a biological organism? (Listen to student ideas.) Each part of an aircraft is designed for a specific purpose. For example, the wings are perfectly shaped to provide lift and the shape of the nose aides the aircraft in slicing through air---just as plants and animals have specific structures and characteristics that suit their functions.

What are some examples of plant and animal adaptations that make them well suited to their environments? (Listen to student answers; possible examples: the long neck of the giraffe for eating from tall trees, long mouthparts of an insect for extracting nectar from flowers.)

How does natural selection result in animals that are perfectly suited to their environments? (Listen to student ideas) Every individual in a population is born with unique random variations in their genes. Some of these random variations confer an advantage that helps the individual survive and reproduce more often than other individuals. In this way, the advantageous genes get passed on more often to offspring, which, over many generations, increases the proportion of that trait in a population.

An important distinction to remember is that the process of natural selection is not goal-oriented, while human inventions are the result of specific, goal-directed research. How can the process of natural selection be applied by engineers to solve engineering design problems? (Listen to student ideas.) Even though the process of natural selection is not-goal-oriented, it results in the increased fitness of organisms in their particular environments because of the differential reproductive success of random variations. Digital organisms are represented by a "genome" of computer commands that each represent a potential solution to a given problem. Engineers determine the parameters of a computational environment and may set constraints on the possible solutions. Then they let the process of natural selection sort through thousands of random variations to determine the "best fit" organisms, which represent the best potential solutions to the problem.

Today you have the opportunity to use the Avida-ED software to engineer and evolve digital organisms. Your challenge: To develop an organism with the highest fitness value. We will hold a competition at the end to determine which organism is the fittest.

Vocabulary/Definitions

Avida-ED: An educational version of the digital evolution software, Avida.

digital evolution: An instance of evolution wherein self-replicating digital organisms are subject to random mutation that is acted on by natural selection.

digital organism: A small, self-replicating computer program.

evolution: The change in the genetic composition of a population from generation to generation.

natural selection: A process in which organisms with certain inherited characteristics are more likely to survive and reproduce than are organisms with other characteristics; the main driving force of evolution.

Procedure

Background

Additional information about the Avida digital life platform including detailed information about the virtual hardware and instruction sets of digital organisms is included in the attached Avida Digital Life Platform Teacher Information. While this level of explanation is not necessary in order for students to manipulate the command sequences of genomes as described in the student handout, computer science teachers may decide to share this information with their students.

Before the Activity

With the Students

  1. Divide the class into small groups, two to three students per computer.
  2. Pass out the student handout. You may wish to demonstrate how to export the command sequence of a digital organism to a text file, edit it, and import it back into Avida-ED.
  3. Set up the activity in one of these ways:
  • Have each group engineer an organism and evolve an organism.
  • Have half the groups evolve an organism and the other half engineer an organism.
  1. Have groups each save their organism of highest fitness and submit them to the instructor by emailing the text file or saving it on a flash drive.
  2. Have teams compose and turn in written answers to the three questions on the handout.
  3. Hold a competition: The instructor competes two to four organisms at the same time using a computer connected to a projector. Idea: Make a "bracket" and have many rounds to determine the winner.
  4. Lead a class discussion to explore students' answers to the three handout discussion questions. See that students make the connection between the computer-simulated organisms and how engineers use computer models to help them determine various iterations of possible solutions.

Attachments

Assessment

Pre-Activity Assessment

Opening Questions: Have students record and turn in their answers to the questions posed and discussed in the Introduction/Motivation section.

  • How do engineers determine the optimum designs for supersonic aircraft?
  • How is the optimum design of aircraft similar to an adaptation of a biological organism?
  • Can you give some examples of plant and animal adaptations that make them well suited to their environments?
  • How does natural selection result in animals that are perfectly suited to their environments?
  • How can the process of natural selection be applied by engineers to solve engineering design problems?
  • Bonus Question: What is the big distinction between processes of natural selection and human invention?

Activity Embedded Assessment

Written Answers: Have students turn in their written answers to the three questions on the Survival of the Fittest Student Handout.

Post-Activity Assessment

Concluding Discussion: Lead a class discussion to explore students' answers to the handout discussion questions. Make sure students make the connection between the computer-simulated organisms and how engineers use computer models to help them determine various iterations of possible solutions.

  • Compare and contrast the process of natural selection and the engineering design process.
  • Did evolved or engineered organisms have an advantage in the class competition? How do you account for these results?
  • Explain how the principles of natural selection can be applied to solve engineering design problems.

Contributors

Wendy Johnson; Jeff Farell

Copyright

© 2013 by Regents of the University of Colorado; original © 2012 Michigan State University

Supporting Program

Bio-Inspired Technology and Systems (BITS) RET, College of Engineering, Michigan State University

Acknowledgements

The contents of this digital library curriculum were developed through the Bio-Inspired Technology and Systems (BITS) RET program under National Science Foundation RET grant no EEG 0908810. However, these contents do not necessarily represent the policies of the NSF and you should not assume endorsement by the federal government.

Last modified: March 7, 2018

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