Evolution of Digital Organisms
Summary
Overview
Engineering Connection
Computer scientists and engineers work together to create software and hardware to model complex systems and create new technologies. The digital evolution software, Avida, was created by a group of computer scientists and software engineers interested in the experimental study of digital organisms in order to better understand how biological natural selection works and then to apply that knowledge to solving computational problems. Evolutionary computation methods can be applied to solve a wide range of engineering design problems, such as the design of self-managing computational systems, robot software, and even the morphological (form and structure) characteristics of robots.
Learning Objectives
After this lesson, students should be able to:
- Compare and contrast digital evolution with biological evolution.
- Discuss the strengths and limitations of using digital evolution software to study biological evolution.
- Discuss how natural selection leads to adaptation both biologically and digitally.
NGSS Alignment
Performance Expectations- HS-LS4-4. Construct an explanation based on evidence for how natural selection leads to adaptation of populations.
- Construct an explanation based on valid and reliable evidence obtained from a variety of sources (including students' own investigations, models, theories, simulations, peer review) and the assumption that theories and laws that describe the natural world operate today as they did in the past and will continue to do so in the future.
- Natural selection leads to adaptation, that is, to a population dominated by organisms that are anatomically, behaviorally, and physiologically well suited to survive and reproduce in a specific environment. That is, the differential survival and reproduction of organisms in a population that have an advantageous heritable trait leads to an increase in the proportion of individuals in future generations that have the trait and to a decrease in the proportion of individuals that do not.
- Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.
- Scientific knowledge is based on the assumption that natural laws operate today as they did in the past and they will continue to do so in the future.
Introduction/Motivation
(In advance, have enough computers for one per student pair, and the ability to download a free software application from the Internet. Alternatively, show the entire class the software with one computer and a projector. Also, make copies of the attached Discussion Questions Handout, one per student, or write the questions on the classroom board.)
What does it mean to be alive? What characteristics do all living things have in common? (Possible answers: Growing, transforming energy, metabolism, genetic information, reproduction, evolution by natural selection, etc.)
What is artificial life? (Possible answers: Inorganic, similarities to biological organisms.) What is a computer virus? (Answer: A computer program that can copy itself and infect a computer.) Is a computer virus alive? (Let students debate and suggest characteristics that are similar and dissimilar to living organisms.)
What do scientists mean when they use the word "evolution"? (Answer: Genetic change in populations over time or change in the proportions of traits in a population over time.) What is required for evolution to occur? (Answers: A variation, reproduction, selection and time.) How do we know that evolution has occurred? (Answers: Examining how a species has changed overtime through fossils.)
We are going to read an article from Discover Magazine that may cause us to change our minds about some of these ideas.
(Continue with the lesson by having students read the article, answer the discussion questions, download and open the software, before proceeding to conduct the two associated activities.)
Pre-Req Knowledge
A basic understanding of evolution by natural selection is required. While the concept of natural selection should have been introduced previously, the associated activities explore how the process works (including variation, inheritance, and selection).
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.Assessment
Writing & Reflection: After reading the article, hold a class discussion guided by the three questions provided in the attached Discussion Questions Handout. Either provide students with the handout so they can write down their ideas individually while reading the article, or have the students copy the questions from the board prior to reading. Have students turn in their written answers to the discussion questions before moving on to conduct the associated activities.
References
McKinley, Philip, Betty H.C. Cheng, Charles Ofria, David Knoester, Benjamin Beckmann, and Heather Goldsby. January 2008. "Harnessing Digital Evolution." IEEE Computer Society. 41 (2008) pp. 54-63. (In digital evolution, self-replicating computer programs—digital organisms—experience mutations and selective pressures, potentially producing computational systems that, like natural organisms, adapt to their environments and protect themselves from threats. Such organisms can help guide the design of computer software.) http://www.cse.msu.edu/~mckinley/digital-evolution.pdf
Zimmer, Carl. "Testing Darwin." Published online February 5, 2005. Discover Magazine, Kalmbach Publishing Co. Accessed May 30, 2012. https://www.discovermagazine.com/technology/testing-darwin
Copyright
2013 by Regents of the University of Colorado; original ©2011 Michigan State UniversityContributors
Wendy Johnson, Robert Pennock, Louise MeadSupporting Program
Bio-Inspired Technology and Systems (BITS) RET, College of Engineering, Michigan State UniversityAcknowledgements
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.
