How Experts Explain Strategic Behavior During Real-Time Strategy Games

Christoph Neumann, Aaron Schnabel, Jonathan Dodge, Ronald A. Metoyer, Simone Stumpf

Real-time strategy games, such as Wargus, are examples of complex learning and planning domains that present unique challenges to AI and machine learning. With the drive to acquire planning knowledge from ever fewer examples, learning and planning in this complex, dynamic environment is challenging. Some headway could be made by providing notations in which an expert can annotate examples to help derive additional knowledge, but describing behavior can be problematic if there is a significant mismatch between the notation and the user's conceptualization of their behavior. We conducted a formative study with expert players of a real-time strategy game to determine the structure of the language used by the experts to describe strategy.

Subjects: 1.11 Planning; 6. Computer-Human Interaction

Submitted: May 15, 2007


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