docs/2016-11-01-inifile.md

@@ -231,14 +231,14 @@ randomly distributed.
 - `patience`:  this parameter influences the route choice behavior when using the quickest path router. 
   It basically defines how long a pedestrian stays in jams before attempting a rerouting.
 
-- `premovement_mean` and `premovement_sigma`: premovement time is Gauss-distributed $$\mathcal{N}(\mu, \sigma^2)$$.
+- `premovement_mean` and `premovement_sigma`: premovement time is Gauss-distributed $`\mathcal{N}(\mu, \sigma^2)`$.
 
 - Risk tolerance can be Gauss-distributed, or beta-distributed. 
-  If not specified then it is defined as $$\mathcal{N}(1, 0)$$:
+  If not specified then it is defined as $`\mathcal{N}(1, 0)`$:
 
-  - `risk_tolerance_mean` and `risk_tolerance_sigma`: $$\mathcal{N}(\mu, \sigma^2)$$.
+  - `risk_tolerance_mean` and `risk_tolerance_sigma`: $`\mathcal{N}(\mu, \sigma^2)`$.
 
-  - `risk_tolerance_alpha` and `risk_tolerance_beta`: $$Beta(\alpha, \beta)$$.
+  - `risk_tolerance_alpha` and `risk_tolerance_beta`: $`Beta(\alpha, \beta)`$.
 
 - `x_min`, `x_max`, `y_min` and `y_max`: define a bounding box where agents should be distributed.
 
@@ -264,10 +264,12 @@ new agents in the system during the simulation.
 - `group_id`: group id of the agents. This `id` should match a predefined group in the section [Agents_distribution](#agents_distribution).
 - `caption`: caption
 - `greedy` (default `false`): returns a Voronoi vertex randomly with respect to weights proportional to squared distances.  
-   For vertexes $$v_i$$ and distances $$d_i$$ to their surrounding seeds
-   calculate the probabilities $$p_i$$ as  
+   For vertexes $`v_i`$ and distances $`d_i`$ to their surrounding seeds
+   calculate the probabilities $`p_i`$ as  
    
-   $$p_i= \frac{d_i^2}{\sum_j^n d_j^2}.$$
+```math
+  p_i= \frac{d_i^2}{\sum_j^n d_j^2}.
+```
    
    If this attribute is set to `true`, the greedy approach is used. 
    That means new agents will be placed on the vertex with the biggest distance to the surrounding seeds.