depends on both the knowledge-like functions, and the likelihood landscape.

More precisely, $c_{ij}$ describes the credibility individual $i$ attributes to individual $j$. If the credibility given to individual $j$ by individual $i$ is high relatively to that one attributed to other individuals (including herself), that means that individual $i$ is more prone to adopt individual $j$’s conceptualization. We will describe in Section 2.6 how this adoption changes one’s knowledge-like function. We also consider that the credibility $c_{ii}$ that an individual $i$ gives to its own categorization can be affected by her own new experiences. In other words, individuals are able of self-criticism. The lower the self-credibility, the more likely an individual is to be influenced by other individuals (self-credibility directly affects an individual’s inertia).

A credibility matrix $C = (c_{ij})_{1 \leq i,j \leq N}$ is a square matrix of size $N$ defined by: $$\label{def:credibilityMin}
    c_{ij} = \max(\Tilde{c}_{ij}, c_{\min}),$$ where $c_{\min} \geq 0$ is a fixed parameter , and

$$\label{def:credibilityMat}
    \Tilde{c}_{ij} = \frac{1}{1 + \mathds{1}_{\{i\neq j\}}\int_{c \in k_j(X)}\, \mathrm{d}c}\exp{\left(\int_{e \in E}\ln{\left(L(e,k_j(e))\mathds{1}_{\{k_i(e)\neq0\}} \right)}\, \mathrm{d}e\right)}.$$

The term $\left (1 + \mathds{1}_{\{i\neq j\}}\int_{c \in k_j(X)}\, \mathrm{d}c \right )^{-1}$ penalizes individuals who use on a wider range of concepts, which means that conceptualization that rely 