We study notions of conditional probability and stochastic dependence/independence in an upgraded probability model in which the space of events is modeled by a full Łukasiewicz tribe of all measurable functions from some measurable space into [0, 1]. Our study is based on properties of joint experiments and the notion of stochastic channel, a construct equivalent to the notion of Markov kernel between two measurable spaces. Using the notion of a degenerated stochastic channel, a channel transmitting no stochastic information between two spaces, we define an asymmetrical independence of random experiments. Finally, we define the notion of conditional probability on full Łukasiewicz tribes.

我们在升级的概率模型中研究条件概率和随机依赖/独立性的概念，在该模型中，事件的空间由所有可测量函数的完整Łukasiewicz部落建模，从某个可测量空间进入[0，1]。我们的研究基于联合实验的性质和随机通道的概念，该结构等同于两个可测量空间之间的马尔可夫核的概念。使用退化的随机信道的概念，即在两个空间之间不传输随机信息的信道，我们定义了随机实验的不对称独立性。最后，我们定义了完整的sukasiewicz部落的条件概率概念。