Suicide, signals, and symbionts : evolving cooperation in agent-based systems
Cooperation is ubiquitous in nature despite the constant pressure for organisms to cheat by receiving a benefit from cooperators, while not cooperating themselves. The continued evolution and persistence of countless forms of cooperation is a central topic in evolutionary theory. Extensive research has been done on the theoretical dynamics of cooperation through game theory and the natural examples of cooperation. However, it remains difficult to understand thoroughly the evolution of many cooperative systems, due in part to the ancient origins of these systems and the long time scales required to see cooperation evolve in any natural populations. I have systematically analyzed the evolution of three broad types of cooperation: programmed cell death, quorum sensing, and mutualisms (cooperation across species). I have provided evidence that programmed cell death can originate due to kin selection. I have also created two new systems to enable the extensive exploration of factors that affect the evolution of public goods cooperation and mutualism. Using these systems, I determine the effects of environmental factors on the evolution of public goods cooperation and mutualism. By uniting the expansive theoretical work on these forms of cooperation with a fully-controlled experimental system, I contributed to our understanding of how these forms of cooperation can emerge and be maintained in industrial and medical applications that rely on bacterial cooperation.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- Attribution-NonCommercial-NoDerivatives 4.0 International
- Material Type
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Theses
- Authors
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Vostinar, Anya E.
- Thesis Advisors
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Ofria, Charles
- Committee Members
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Waters, Chris
Punch, William
Adami, Christoph
- Date
- 2017
- Subjects
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Kin selection (Evolution)
Computer simulation
Quorum sensing (Microbiology)
Mutualism (Biology)
Natural selection
- Program of Study
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Computer Science - Doctor of Philosophy
- Degree Level
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Doctoral
- Language
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English
- Pages
- xii, 124 pages
- ISBN
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9780355079920
0355079925
- Permalink
- https://doi.org/doi:10.25335/nn8e-0d08