In a network of reinforced stochastic processes, for certain values of the parameters, all the agents' inclinations synchronize and converge almost surely toward a certain random variable. The present work aims at clarifying when the agents can asymptotically polarize, i.e. when the common limit inclination can take the extreme values, 0 or 1, with probability zero, strictly positive, or equal to one. Moreover, we present a suitable technique to estimate this probability that, along with the theoretical results, has been framed in the more general setting of a class of martingales taking values in [0, 1] and following a specific dynamics.

翻译：在强化随机过程网络中，对于某些参数值，所有主体的倾向同步并几乎必然收敛于某个随机变量。本研究旨在阐明主体何时能够渐近极化，即公共极限倾向取极值0或1的概率为零、严格正或等于一的情形。此外，我们提出了一种适用于估计该概率的技术，该技术与理论结果一同被纳入更一般的框架中，即一类取值于[0, 1]且遵循特定动态的鞅。