Abstract
Interactions among game units can be conveniently described by fuzzy measures and integrals. Focusing on Warcraft, there are several good results of unit selection strategy evaluation for a genetic algorithm that search in plan space. However, this kind of evaluators are suffered from high complexity in fuzzy measure determination. In this paper, we novelly combine Extreme Learning Machine(ELM) and Fuzzy Integral(FI) to achieve a fast evaluation of game strategy. Experimental comparison demonstrates the effectiveness of the proposed method in both time and accuracy.
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Li, Y., Ng, P.H.F., Shiu, S.C.K. (2013). Rapid Game Strategy Evaluation Using Fuzzy Extreme Learning Machine. In: Maji, P., Ghosh, A., Murty, M.N., Ghosh, K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2013. Lecture Notes in Computer Science, vol 8251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45062-4_34
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DOI: https://doi.org/10.1007/978-3-642-45062-4_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45061-7
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