Scale-free adaptive planning for deterministic dynamics & discounted rewards
PlaTγPOOS is an adaptive planning algorithm that improves upon Open-Loop Optimistic Planning by dynamically adjusting its behavior when reward and noise ranges are unknown. It uses a scale-free optimization strategy to efficiently plan in environments with deterministic dynamics and stochastic discounted rewards, achieving superior learning rates.