Back to the Future: Solving Hidden Parameter MDPs with Hindsight

Exploring the Effects of Conditioning Independent Q-Learners on the Sufficient Statistic for Dec-POMDPs

In this study, we investigate the effects of conditioning Independent Q-Learners (IQL) not solely on the individual action-observation history, but additionally on the sufficient plan-time statistic for Decentralized Partially Observable Markov Decision Processes. In doing so, we attempt to address a key shortcoming of IQL, namely that it is...

Online reinforcement learning control for aerospace systems

Reinforcement Learning (RL) methods are relatively new in the field of aerospace guidance, navigation, and control. This dissertation aims to exploit RL methods to improve the autonomy and online learning of aerospace systems with respect to the a priori unknown system and environment, dynamical uncertainties, and partial observability. In the...