Explaining how to play real-time strategy games

Authors:
Ronald Metoyer;Simone Stumpf;Christoph Neumann;Jonathan Dodge;Jill Cao;Aaron Schnabel
Affiliations:
Oregon State University, Corvallis, OR 97331, USA;Oregon State University, Corvallis, OR 97331, USA;Hewlett Packard, Corvallis, OR 97330, USA;Oregon State University, Corvallis, OR 97331, USA;Oregon State University, Corvallis, OR 97331, USA;9Wood, Inc., Springfield, OR 97477, USA
Venue:
Knowledge-Based Systems
Year:
2010

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Abstract

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.