Abstract: Recursive distributional equations (RDE) appear in various areas of probability such as the probabilistic analysis of algorithms, probabilistic number theory, stochastic geometry or, more recently, in distributional reinforcement learning (DRL). In this talk more applied aspects of RDE are discussed in the context of their applications. Some of the new results discussed on DRL are joint work with Julian Gerstenberg and Denis Spiegel.