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@@ -6,11 +6,28 @@ _Yet another black-box optimization library for Python_
 
 ## Description
 
-Yabox is a small library for black-box (derivative free) optimization of functions. The library includes different stochastic algorithms for minimizing a function f(X), where X = {x1, ..., xN}. The function f(X) does not need to have an analytical form.
+Yabox is a very small library for black-box (derivative free) optimization of functions that only depends on `numpy` and `matplotlib` for visualization. The library includes different stochastic algorithms for minimizing a function `f(X)`  that does not need to have an analytical form, where `X = {x1, ..., xN}`.
 The current version of the library includes the Differential Evolution algorithm and a modified version for parallel evaluation.
 
 Example of minimization of the Ackley function (using Yabox and Differential Evolution):
 
 ![Ackley Function](../master/notebooks/img/ackley.gif?raw=true)
 
+## Basic usage
+
+### Pre-defined functions
+Yabox includes some default benchmark functions used in black-box optimization, available in the package yabox.problems. These functions also include 2D and 3D plotting capabilities:
+
+```python
+from yabox.problems import CrossInTray
+cross = CrossInTray()
+cross.plot3d()
+```
+![CrossInTray Function](../master/docs/images/crossintray.png?raw=true)
+
+### Optimization
+
+Example using Differential Evolution
+
+![Optimization example](../master/docs/images/opt_example.gif?raw=true)
 
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