  Kiiking is an extreme sport in which athletes alternate between standing and
squatting to pump a standing swing till it is inverted and completes a
rotation. A minimal model of the sport may be cast in terms of the control of
an actively driven pendulum of varying length to determine optimal strategies.
We show that an optimal control perspective, subject to known biological
constraints, yields time-optimal control strategy similar to a greedy algorithm
that aims to maximize the potential energy gain at the end of every cycle. A
reinforcement learning algorithms with a simple reward is consistent with the
optimal control strategy. When accounting for air drag, our theoretical
framework is quantitatively consistent with experimental observations while
pointing to the ultimate limits of kiiking performance.
