21 citations · 149 across the 34 of their papers we have counts for
3 papers · 1 filter
Meta-descent for Online, Continual Prediction
Andrew Jacobsen, Matthew Schlegel, Cameron Linke +3
This paper investigates different vector step-size adaptation approaches for non-stationary online, continual prediction problems. Vanilla stochastic gradient descent can be consid…
Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study
Cam Linke, Nadia M. Ady, Martha White +2
Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the env…
Planning with Expectation Models
Yi Wan, Zaheer Abbas, Adam White +2
Distribution and sample models are two popular model choices in model-based reinforcement learning (MBRL). However, learning these models can be intractable, particularly when the…