Explaining How to Play Real-Time Strategy Games

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. Key words: strategy, explanation, real-time games, user study

• Type: Conference
• Year: 2009
• Where: SGAI
• Authors: Ronald A. Metoyer, Simone Stumpf, Christoph Neumann, Jonathan Dodge, Jill Cao, Aaron Schnabel
• Keywords: Artificial Intelligence, Experienced Real-time Strategy, Real-time Strategy Game, SGAI 2009, Users Explain Game