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Selectively Reactive Coordination for a Team of Robot Soccer Champions

AAAI 2016 · Multi-agent systems and games › Games and equilibria · approach: Learning in Markov games · 24 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace individually-optimal field-wide positioning with zone-constrained coordination (SRC) (ablation)CMDragons offense · Simulation vs IndivOptgoals scored: 35 -> 59Helped
replace exact team plan (fixed locations) with zone skeleton plus individual reactive positioning (SRC) (ablation)CMDragons offense · Simulation vs ExactPlangoals scored: 53 -> 67Helped
SRC versus ExactPlan on total shots (ablation)CMDragons offense · Simulation vs ExactPlantotal shots: 2648 -> 2227Hurt
SRC versus IndivOpt on total shots (ablation)CMDragons offense · Simulation vs IndivOpttotal shots: 1501 -> 1823Helped
add dribble action with constant scoring-probability estimatePrimary Attacker · RoboCup 2015 semi-final and finaladditional ball possession time: 47 and 146 secondsHelped

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