论文标题
熵多人口动态系统的平均场限制
Mean-field limits for entropic multi-population dynamical systems
论文作者
论文摘要
在一般假设集中，证明了具有熵正则化及其融合到合适的均值近似的多人群动力系统的适当性。在对标签演变的进一步假设下，考虑了代理位置和标签之间的不同时间尺度的情况。极限系统将位置空间中的平均场型演变融合在一起，并在标签空间中对收益功能进行瞬时优化。
The well-posedness of a multi-population dynamical system with an entropy regularization and its convergence to a suitable mean-field approximation are proved, under a general set of assumptions. Under further assumptions on the evolution of the labels, the case of different time scales between the agents' locations and labels dynamics is considered. The limit system couples a mean-field-type evolution in the space of positions and an instantaneous optimization of the payoff functional in the space of labels.
