The transition function in a Markov decision process
The notation $T\colon A\times U\times A\to[0,\infty)$ means a function with three parameters, the first from $A$, the second from $U$, and the third from $A$, which outputs a non-negative real.

It is somewhat strange that the range is stated as $[0,\infty)$ rather than $[0,1]$. In fact, a perhaps better way of thinking of $T$ is as a function from $A \times U$ to the set of distributions over $A$. That is, $T$ gets a state and an action, and outputs a distribution over the set of states.

The semantics of $T$ are as follows: when at state $a$ and performing action $u$, the probability of moving to state $b$ is $T(a,u,b)$. Thus for all $a \in A$ and $u \in U$ we must have $\sum_{b \in A} T(a,u,b) = 1$.