In Chap. 2 we introduced constraint satisfaction approaches to PCG. Recall that constraint-based approaches use a set of variables, each with a range of possible values, and a set of constraints that must be satisfied over the variables and outputs. In Sect. 2.2 we walked through an example of how we could formulate the problem of generating palindromic words as a constraint satisfaction problem. Constraint-based PCG approaches typically require the encoding of human design and domain knowledge into the set of variables, values, and constraints. For example, when formulating the palindrome problem we encoded the knowledge that the letters at position t and length—t need to be the same and the knowledge of which sequences of letters result in valid words.