Abstract
A good evaluation function is needed for a good game program, and good features, which are primitive metrics of a state, are needed for a good evaluation function. In order to obtain good features, automatic generation of features by machine learning is promising. However, the generated features are usually written in logic programs, whose evaluation is much slower than that of other native expressions due to the interpretive evaluation of the logic programs. In order to solve this problem, we propose a method which constructs a specialized evaluator using a combination of techniques: partial evaluation, Boolean tables, and incremental calculation. It exhaustively unfolds logical programs until they can be represented as simple Boolean tables. The constructed specialized evaluator is efficient since it consults only these compiled tables. Experiments with Othello showed that speed can be increased approximately 2,000 times.
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Kaneko, T., Yamaguchi, K., Kawai, S. (2000). Compiling Logical Features into Specialized State-Evaluators by Partial Evaluation, Boolean Tables and Incremental Calculation. In: Mizoguchi, R., Slaney, J. (eds) PRICAI 2000 Topics in Artificial Intelligence. PRICAI 2000. Lecture Notes in Computer Science(), vol 1886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44533-1_11
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DOI: https://doi.org/10.1007/3-540-44533-1_11
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