Optimizing Propositional Networks
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General Game Playing (GGP) programs need a Game Description Language (GDL) reasoner to be able to interpret the game rules and search for the best actions to play in the game. One method for interpreting the game rules consists of translating the GDL game description into an alternative representation that the player can use to reason more efficiently on the game. The Propositional Network (PropNet) is an example of such method. The use of PropNets in GGP has become popular due to the fact that PropNets can speed up the reasoning process by several orders of magnitude compared to custom-made or Prolog-based GDL reasoners, improving the quality of the search for the best actions. This paper analyzes the performance of a PropNet-based reasoner and evaluates four different optimizations for the PropNet structure that can help further increase its reasoning speed in terms of visited game states per second.
This work is funded by the Netherlands Organisation for Scientific Research (NWO) in the framework of the project GoGeneral, grant number 612.001.121.
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