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Author Park, Hyunsoo ♦ Cho, Hochul ♦ Kim, Kyung-Joong ♦ Kim, Chang-Yeun
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF ♦ HTM / HTML
Language English
Subject Keyword Real-time strategy game ♦ Strategy prediction ♦ Ai bots ♦ Machine learning ♦ Fog of war ♦ Starcraft
Abstract StarCraft is a well-known real-time strategy game developed by Blizzard Entertainment in 1998. One of the characteristics of this game is “fog of war,” which refers to the fact that players cannot see their opponents' regions but only their own unit. This characteristic of the game means that the information required in order to predicting the opponent's strategy is only available through “scouting.” Although the “fog of war” is one of the most important features of the game, it has not been deeply understood in the design of artificial intelligence. In this work, we propose to investigate the effect of the “fog of war” in the prediction of opponent's strategy using machine learning for human players and artificial intelligence (AI) bots. To realize this analysis, we develop a customized replay analyzer that exports the internal game events with/without the fog of war. In the experimental results, we collect replays from various sources: human vs. human, human vs. AI bots, and AI bots vs. AI bots. This systematic analysis with “fog of war” reveals the predictability of the machine-learning algorithms on different conditions and the directions for designing new artificial intelligence for the game.
Description Affiliation: Sejong University, Gwangjin-gu, Seoul, Republic of Korea (Cho, Hochul; Park, Hyunsoo; Kim, Chang-Yeun; Kim, Kyung-Joong)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-03-01
Publisher Place New York
Journal Computers in Entertainment (CIE) (CIE)
Volume Number 14
Issue Number 1
Page Count 16
Starting Page 1
Ending Page 16

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Source: ACM Digital Library