 100 agents are arranged on a \(10 \times 10\) lattice such as that illustrated in  Figure 3.  Each agent is connected to four others: top, bottom, left, and right. The exceptions are those at the edges or corners of the array, connected to only three and two neighbors, respectively. Agents in the model have multiple cultural “features”, each of which carries one of multiple possible “traits”. One can think of the features as categorical variables and the traits as options or values within each category. For example, the first feature might represent culinary tradition, the second one the style of dress, the third music, and so on. In the base configuration an agent’s “culture” is defined by five features \((F = 5)\) each having one of 10 traits \((q =10),\) numbered 0 through 9. Agent x might have \(\langle 8, 7, 2, 5, 4\rangle\) as a cultural signature while agent y is characterized \(\langle 1, 4, 4, 8, 4\rangle\). Agents are fixed in their lattice location and hence their interaction partners. Agent interaction and imitation rates are determined by neighbor similarity, where similarity is measured as the percentage of feature positions that carry identical traits. With five features, if a pair of agents share exactly one such element they are 20% similar; if two elements match then they are 40% similar, and so forth. In the example just given, agents x and y and have a similarity of 20% because they share only one feature.