arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2410.22010q-bio.PEmath.DSmath.PR
收藏

具有随机收益矩阵的演化动力学

Evolutionary dynamics with random payoff matrices

Manh Hong Duong, The Anh Han

AI总结:

该观点文章针对演化博弈论应用中普遍存在的不确定性问题,综述了带随机收益矩阵的演化动力学相关文献(重点为连续模型),并提出该领域未来研究的挑战性开放问题。

摘要:

以随机性和随机波动性为特征的不确定性,在演化博弈论跨生物学、经济学和社会科学等各领域的应用中普遍存在。这类不确定性可源于波动环境、行为误差或信息不完全等多种来源。将不确定性纳入演化模型,对提升其对现实问题的适用性至关重要。在这篇观点文章中,我们综述了关于带随机收益矩阵的演化动力学的相关文献,重点关注连续模型,并针对这一重要领域的未来研究提出了具有挑战性的开放问题。

英文摘要:

Uncertainty, characterised by randomness and stochasticity, is ubiquitous in applications of evolutionary game theory across various fields, including biology, economics and social sciences. The uncertainty may arise from various sources such as fluctuating environments, behavioural errors or incomplete information. Incorporating uncertainty into evolutionary models is essential for enhancing their relevance to real-world problems. In this perspective article, we survey the relevant literature on evolutionary dynamics with random payoff matrices, with an emphasis on continuous models. We also pose challenging open problems for future research in this important area.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑