On Emergence of Scalable Tactical and Strategic Behavior

The principle of behavioral programming [1] suggests to derive low-level controllers from symbolic high-level task descriptions in a predictable way. This paper presents an extension of the principle of behavioral programming -- by identifying a feedback link between emergent behaviour and a scalable Deep Behaviour Projection (DBP) agent architecture. In addition, we introduce a new variant of the RoboCup Synthetic Soccer, called Circular Soccer. This variant simulates matches among multiple teams on a circular field, and extends the RoboCup Simulation towards strategic game-theoretic issues. Importantly, the Circular Soccer world provides a basis for an architecture scale-ability evaluation, and brings us closer to the idea of meta-game simulation.