Add licensing information, and proper description of support_enumerat…

…ion function

LICENSE.md

@@ -0,0 +1,7 @@
+Copyright (c) 2012 Jakub Konka
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

README.md

@@ -1,4 +1,13 @@
 py-game-theory
 ==============
 
-Python library for solving finite games
+Python library implementing algorithms for solving games (as defined in game theory), written in py3k.
+
+This is a work in progress. Pull requests, forks, comments, and suggestions are very welcomed.
+
+Required modules:
+
++ [NumPy](http://numpy.scipy.org/)
+
+# License
+License information can be found in [LICENSE.md](LICENSE.md).

simultaneous_move/bimatrix.py → normal_form/bimatrix.py

@@ -2,6 +2,16 @@
 import numpy as np
 
 def support_enumeration(payoff_matrix_p1, payoff_matrix_p2):
+  r"""Implements support enumeration algorithm for computing all Nash equilibria of a bimatrix game specified by the input payoff matrices per player, and returns a list consisting of all Nash equilibria of the game. Each element of the returned list is a tuple of mixed strategies for both players, with the first element being the mixed strategy of the first player.
+  
+  Full theoretical description of the algorithm can be found in \"Algorithmic Game Theory\" by Nisan et al. (see Algorithm 3.4).
+  
+  IMPORTANT: The algorithm requires the game to be _nondegenerate_.
+  
+  Keyword arguments:
+  payoff_matrix_p1 -- Payoff matrix of player 1
+  payoff_matrix_p2 -- Payoff matrix of player 2
+  """
   # Assumes matrices are nondegenerate!
   # Input params
   m, n = payoff_matrix_p1.shape