In-game action list segmentation and labeling in real-time strategy games

In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses....

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Main Authors: GONG, Wei, LIM, Ee-Peng, ACHANANUPARP, Palakorn, ZHU, Feida, LO, David, CHUA, Freddy Chong-Tat
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Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/sis_research/3482
https://ink.library.smu.edu.sg/context/sis_research/article/4483/viewcontent/C29___In_Game_Action_List_Segmentation_and_Labeling_in_Real_Time_Strategy_Games__CIG2012_.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-44832017-09-18T09:24:51Z In-game action list segmentation and labeling in real-time strategy games GONG, Wei LIM, Ee-Peng ACHANANUPARP, Palakorn ZHU, Feida LO, David CHUA, Freddy Chong-Tat In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as high as 98.9%. 2012-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3482 info:doi/10.1109/CIG.2012.6374150 https://ink.library.smu.edu.sg/context/sis_research/article/4483/viewcontent/C29___In_Game_Action_List_Segmentation_and_Labeling_in_Real_Time_Strategy_Games__CIG2012_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer games Feature extraction Conditional random fields Feature extraction Human annotation In-game action list segmentation Real-time strategy games Semantic label assignment Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer games
Feature extraction
Conditional random fields
Feature extraction
Human annotation
In-game action list segmentation
Real-time strategy games
Semantic label assignment
Databases and Information Systems
spellingShingle Computer games
Feature extraction
Conditional random fields
Feature extraction
Human annotation
In-game action list segmentation
Real-time strategy games
Semantic label assignment
Databases and Information Systems
GONG, Wei
LIM, Ee-Peng
ACHANANUPARP, Palakorn
ZHU, Feida
LO, David
CHUA, Freddy Chong-Tat
In-game action list segmentation and labeling in real-time strategy games
description In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as high as 98.9%.
format text
author GONG, Wei
LIM, Ee-Peng
ACHANANUPARP, Palakorn
ZHU, Feida
LO, David
CHUA, Freddy Chong-Tat
author_facet GONG, Wei
LIM, Ee-Peng
ACHANANUPARP, Palakorn
ZHU, Feida
LO, David
CHUA, Freddy Chong-Tat
author_sort GONG, Wei
title In-game action list segmentation and labeling in real-time strategy games
title_short In-game action list segmentation and labeling in real-time strategy games
title_full In-game action list segmentation and labeling in real-time strategy games
title_fullStr In-game action list segmentation and labeling in real-time strategy games
title_full_unstemmed In-game action list segmentation and labeling in real-time strategy games
title_sort in-game action list segmentation and labeling in real-time strategy games
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/3482
https://ink.library.smu.edu.sg/context/sis_research/article/4483/viewcontent/C29___In_Game_Action_List_Segmentation_and_Labeling_in_Real_Time_Strategy_Games__CIG2012_.pdf
_version_ 1770573231217967104