Any modeling of a dynamical system consists of keeping some information and discarding some other information, for example, is a gas molecule modeled as a point or a ball or a more complicated structure? In topological dynamics the information retained is the "closeness'' of world-states, specified for instance, by a distance function $d(x,y)$ between all pairs $x,y$ of worlds-states. In ergodic theory the information retained is the relative probability of different world-states. More technically, for us a topological dynamical system (t.d.s), will be given by a compact metric space $(X,d)$ and a homeomorphism (continuous invertible map) $T:X\rightarrow T$. $X$ represents the phase space and $T$ represents the evaluation rule. The metric $d:X\times X\rightarrow\mathbb{{R}}$ is the distance function.
A fundamental problem in the theory of dynamical systems is the problem of deciding if two given systems are isomorphic ("the same''). A very powerful tool is given by invariants. For example, an invariant can be given by a series of steps which you apply to a dynamical system, and which result with some quantity (e.g. a real number). This procedure must have the property, that if you apply the same steps to another system, which is actually isomorphic to the first system, but its real-world manifestation is say very different, then you get exactly the same quantity. This property is referred to as invariance and that is why invariants are called invariants. A major invariant for topological dynamical systems is the invariant of topological entropy. You can read about it here. We would like to introduce the invariant of mean dimension so we first need to answer the question: