Abstract
In this work we investigate the potential of combining AI tree-search algorithms with the algorithms of combinatorial game theory to provide more efficient strategies for playing sum games based on subgame types. Two new approximate strategies are developed and tested using a specified game model. Both strategies achieve higher performance than approximate strategies previously proposed in the literature without being computationally more expensive.
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