Tudge, Simon, James (2016) Game theoretic treatments of social niche construction: How do the conditions for cooperation evolve? University of Southampton, Doctoral Thesis, 105pp.
Abstract
The presence of cooperation has long puzzled evolutionary biologists; the resolution to this puzzle is often attributed to population structure. While the effects of population structure on cooperation are understood, less is known regarding how population structure is itself subject to evolution. The research program of Social Niche Construction (SNC) explores these issues. This thesis presents three related papers that further our understanding of SNC and addresses a number of issues within the research program.
Firstly, I demonstrate that diploid organisms under the presence of meiotic drive represents an example of SNC; where assortative mating plays the role of the social niche modifier. I thus argue that assortative mating may be an adaptation that overcomes meiotic drive.
Secondly, I present a formal argument for why a gene that causes individuals to assort cannot invade a population of freely-mixed defectors at equilibrium. I present a potential solution to this problem; namely, that if individuals engage in multiple simultaneous cooperative dilemmas, then there may be a continued selection pressure for increased assortment.
Lastly, I present a model for the evolution of a cooperative division of labour. Previous gametheoretic definitions assume cooperation to be a single behaviour. I argue that this is too narrow, as often the benefits of cooperation come about through the interaction of differing types. To address this issue I define a class of games; which I call Division of Labour (DOL) games, that have the property that fitness is maximised by a mixture of different types. I show that DOL games are not resolved by a positive assortment on phenotype; instead mean fitness is maximised by positive assortment on a genotype that can exhibit phenotypic plasticity; i.e. express multiple phenotypes conditionally upon social environment.
Together these models broaden and deepen our understanding of how population structure evolves and how SNC transforms social dilemmas and modifies social outcomes.
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- Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Electronics & Computer Science (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg)
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