Figure 5.

(a) The workings of a hierarchical algorithm with 3 parents and 3 child patterns per parent. The different lines of squares/circles correspond to the different units in parents/children. Colors correspond to active Potts states while white denotes the quiescent states. $S=3$. (b) The workings of the multi-parent algorithm with $\Pi =3$ parents and $p_{par}=3$ child patterns per parent and 5 total child patterns. Black arrows and their thickness denote strength of input. The main difference with the hierarchical algorithm is that each child pattern can receive input from multiple parents. If each parent is to represent a feature and each child a concept, the algorithm entails the generation of a concept from multiple features.