Dynamic Properties of Evolutionary Multi-player Games in Finite Populations
William D. Hamilton famously stated that â€œhuman life is a many person game and not just a disjoined collection of two person gamesâ€ . However, most of the theoretical results in evolutionary game theory have been developed for two player games. In spite of a multitude of examples ranging from humans to bacteria, multi-player games have received less attention than pairwise games due to their inherent complexity. Such complexities arise from the fact that group interactions cannot always be considered as a sum of multiple pairwise interactions. Mathematically, multi-player games provide a natural way to introduce non-linear, polynomial fitness functions into evolutionary game theory, whereas pairwise games lead to linear fitness functions. Similarly, studying finite populations is a natural way of introducing intrinsic stochasticity into population dynamics. While these topics have been dealt with individually, few have addressed the combination of finite populations and multi-player games so far. We are investigating the dynamical properties of evolutionary multi-player games in finite populations. Properties of the fixation probability and fixation time, which are relevant for rare mutations, are addressed in well mixed populations. For more frequent mutations, the average abundance is investigated in well mixed as well as in structured populations. While the fixation properties are generalizations of the results from two player scenarios, addressing the average abundance in multi-player games gives rise to novel outcomes not possible in pairwise games.
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- Maciej Bukowski & Jacek Miekisz, 2004. "Evolutionary and asymptotic stability in symmetric multi-player games," International Journal of Game Theory, Springer;Game Theory Society, vol. 33(1), pages 41-54, January.
- Drew Fudenberg & Lorens A. Imhof, 2004.
"Imitation Processes with Small Mutations,"
Harvard Institute of Economic Research Working Papers
2050, Harvard - Institute of Economic Research.
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