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 # PyCGA
 
-PyCGA is a simple implementation of Compact Genetic Algorithm (cGA) written in Python. It implements a simple OneMax fitness function and a trap-5, as well as a (very simple and very biased) method of solving the said trap. PyCGA can also plot simple graphs showing how the fitness score and the state of each member inside the probability vector change as our algorithm "evolves" through generations. 
+PyCGA is a simple implementation of Compact Genetic Algorithm (cGA) written in Python for educational purposes. It implements a simple OneMax fitness function and a trap-5, as well as a (very simple and very biased) method of solving the said trap. PyCGA can also plot simple graphs showing how the fitness score and the state of each member inside the probability vector change as our algorithm "evolves" through generations. 
 
 ## Dependencies
 
-- [matplotlib] [3] for graph plotting
+- [Python] [5] version 2.7.3 or any later version in the Python 2.7 series
+- [matplotlib] [3] (optional) for graph plotting
+
+## Usage
+
+Just invoke PyCGA in your favorite terminal emulator like the following examples:
+    
+    python PyCGA.py
+
+or
+
+    ./PyCGA.py
+
+should be more than enough to start PyCGA with the default parameters.
+
+For more information, such as how to change various parameters of PyCGA, please see PyCGA's help, which can be shown using the following commands:
+
+    python PyCGA.py --help
+
+or
+
+    ./PyCGA.py --help
 
 ## References
 
 [2]: http://www.cleveralgorithms.com/nature-inspired/probabilistic/compact_genetic_algorithm.html
 [3]: http://matplotlib.org
 [4]: http://www.cleveralgorithms.com
+[5]: http://www.python.org