evolution - a simulation alexander liu eric chang advisor: professor amit sahai thursday, october...

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Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while at once powerful and far-reaching, is admittedly a difficult topic to experiment upon. Countless generations of living things over timescales of millions of years make it next-to-impossible to observe. Thankfully, modeling digital organisms inside a simulated environment enables scientists to focus on the particular aspects of evolution they wish to study, and to note parallels between the transformations these life-forms can undertake and those of their real-life counterparts. While we are not the first to act upon this idea, we wish to use the advantages it confers to study two areas of particular interest, and to come up with answers that will hopefully contribute to those evolutionary issues.

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Page 1: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while

Evolution - a Simulation

Alexander LiuEric Chang

Advisor: Professor Amit SahaiThursday, October 25, 2pm: 4750 Boelter Hall

The theory of evolution, while at once powerful and far-reaching, is admittedly a difficult topic to experiment upon. Countless generations of living things over timescales of millions of years make it next-to-impossible to observe. Thankfully, modeling digital organisms inside a simulated environment enables scientists to focus on the particular aspects of evolution they wish to study, and to note parallels between the transformations these life-forms can undertake and those of their real-life counterparts. While we are not the first to act upon this idea, we wish to use the advantages it confers to study two areas of particular interest, and to come up with answers that will hopefully contribute to those evolutionary issues.

Page 2: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while

Alex

Page 3: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while
Page 4: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while
Page 5: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while

Parthenogenesis

• Definition

• Parthenogenesis in real-world organisms

• Advantages and disadvantages

Page 6: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while

Experimentation

• What aspect of this trait are we examining, and what kind of results do we hope to achieve?

• How would mutation and selection factor into the simulation?

• How would the characteristics of such organisms be modeled?

Page 7: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while

How to model experiments

• Building the software framework

• Modeling the organisms and variations within the population

• Representing parthenogenesis and how it affects fitness

Page 8: Evolution - a Simulation Alexander Liu Eric Chang Advisor: Professor Amit Sahai Thursday, October 25, 2pm: 4750 Boelter Hall The theory of evolution, while

Tentative Timeline

Fall Quarter end: Have a working software framework with within which we could implement our experiments. This framework may have to be modified further on as fit as we proceed.

Winter Quarter mid: Have at least the core experiments up and running within the software model. Given unsatisfactory results, revise (and rebuild) as needed. Otherwise, expand upon existing project ideas in new directions.

Winter Quarter end: Ideally, have concrete, satisfactory results with the core experiments. The software should be in its final stages and able to simulate the experiments.

Spring Quarter mid: Possibly branch off in related directions and act on our findings. Begin preparing discussion and paper of our results.

Spring Quarter end: Completion of the project. All results should have been finalized and any relevant findings set down.