In IJCAI Workshop on Algorithmic Game Theory (AGT). 2015.
This is the author's version of the work.
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Abstract
Normal form games are one of the most familiar representations for
modeling interactions among multiple agent. However, modeling many realistic
interactions between agents results in games that are extremely large. In these
cases computing standard solutions like Nash equilibrium may be intractable. To
overcome this issue the idea of abstraction has been investigated,
most prominently in research on computer Poker. Solving a
game using abstraction requires using some method to simplify the game before it is analyzed. We study a new
variation for solving normal form games using abstraction that is based on finding
and solving suitable sub games. We compare this method with several variations
of a common type of abstraction based on clustering similar strategies.
