Rapid game strategy evaluation using fuzzy extreme learning machine

Ying Jie Li, Peter Hiu Fung Ng, Chi Keung Simon Shiu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

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.
Original languageEnglish
Title of host publicationPattern Recognition and Machine Intelligence - 5th International Conference, PReMI 2013, Proceedings
Pages250-255
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2013
Event5th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2013 - Kolkata, India
Duration: 10 Dec 201314 Dec 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8251 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2013
Country/TerritoryIndia
CityKolkata
Period10/12/1314/12/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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