TY - JOUR
T1 - Explaining how to play real-time strategy games
AU - Metoyer, Ronald
AU - Stumpf, Simone
AU - Neumann, Christoph
AU - Dodge, Jonathan
AU - Cao, Jill
AU - Schnabel, Aaron
N1 - Funding Information:
The authors would like to thank the study participants and gratefully acknowledge support of the Defense Advanced Research Projects Agency under DARPA Grant No. FA8650-06-C-7605 . Views and conclusions contained in this document are those of the authors and do not necessarily represent the official opinion or policies, either expressed or implied of the US government or of DARPA.
PY - 2010/5
Y1 - 2010/5
N2 - Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End-user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.
AB - Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End-user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.
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U2 - 10.1016/j.knosys.2009.11.006
DO - 10.1016/j.knosys.2009.11.006
M3 - Article
AN - SCOPUS:77950596112
SN - 0950-7051
VL - 23
SP - 295
EP - 301
JO - Knowledge-Based Systems
JF - Knowledge-Based Systems
IS - 4
ER -