Mathematical and Computational Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, 85287, USA.
National Center for Biotechnology Information, National Institutes of Health, Bldg. 38A, 8600, Rockville Pike, Bethesda, MD, 20894, USA.
Bull Math Biol. 2019 Jul;81(7):2117-2132. doi: 10.1007/s11538-019-00592-2. Epub 2019 Apr 23.
Evolutionary game theory has been used extensively to study single games as applied to cancer, including in the context of metabolism, development of resistance, and even games between tumor and treatment. However, the situation when several games are being played against each other at the same time has not yet been investigated. Here, we describe a mathematical framework for analyzing natural selection not just between strategies, but between games. We provide theoretical analysis of situations of natural selection between the games of Prisoner's dilemma and Hawk-Dove, and demonstrate that while the dynamics of cooperators and defectors within their respective games is as expected, the distribution of games changes over time due to natural selection. We also investigate the question of mutual invasibility of games with respect to different strategies and different initial population composition. We conclude with a discussion of how the proposed approach can be applied to other games in cancer, such as motility versus stability strategies that underlie the process of metastatic invasion.
进化博弈论被广泛应用于研究应用于癌症的单场博弈,包括在代谢、耐药性发展甚至肿瘤与治疗之间的博弈的背景下。然而,同时进行多场博弈的情况尚未被研究过。在这里,我们描述了一个用于分析自然选择的数学框架,不仅是在策略之间,而且是在博弈之间。我们对囚徒困境和鹰鸽博弈之间的自然选择情况进行了理论分析,并证明,尽管各自游戏中的合作者和背叛者的动态与预期相符,但由于自然选择,游戏的分布会随时间而变化。我们还研究了关于不同策略和不同初始种群组成的游戏相互可入侵性的问题。最后,我们讨论了如何将所提出的方法应用于癌症中的其他博弈,例如运动性与稳定性策略,这些策略是转移性入侵过程的基础。