TY - GEN
T1 - Rapid game strategy evaluation using fuzzy extreme learning machine
AU - Li, Ying Jie
AU - Ng, Peter Hiu Fung
AU - Shiu, Chi Keung Simon
PY - 2013/12/1
Y1 - 2013/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84893416146&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-45062-4_34
DO - 10.1007/978-3-642-45062-4_34
M3 - Conference article published in proceeding or book
SN - 9783642450617
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 250
EP - 255
BT - Pattern Recognition and Machine Intelligence - 5th International Conference, PReMI 2013, Proceedings
T2 - 5th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2013
Y2 - 10 December 2013 through 14 December 2013
ER -