93 citations · 487 across the 42 of their papers we have counts for
5 papers · 1 filter
MaestroMotif: Skill Design from Artificial Intelligence Feedback
Martin Klissarov, Mikael Henaff, Roberta Raileanu +7
Describing skills in natural language has the potential to provide an accessible way to inject human knowledge about decision-making into an AI system. We present MaestroMotif, a m…
Plastic Learning with Deep Fourier Features
Alex Lewandowski, Dale Schuurmans, Marlos C. Machado
Deep neural networks can struggle to learn continually in the face of non-stationarity. This phenomenon is known as loss of plasticity. In this paper, we identify underlying princi…
Demystifying the Recency Heuristic in Temporal-Difference Learning
Brett Daley, Marlos C. Machado, Martha White
The recency heuristic in reinforcement learning is the assumption that stimuli that occurred closer in time to an acquired reward should be more heavily reinforced. The recency heu…
Learning Continually by Spectral Regularization
Alex Lewandowski, Michał Bortkiewicz, Saurabh Kumar +4
Loss of plasticity is a phenomenon where neural networks can become more difficult to train over the course of learning. Continual learning algorithms seek to mitigate this effect…
Averaging -step Returns Reduces Variance in Reinforcement Learning
Brett Daley, Martha White, Marlos C. Machado
Multistep returns, such as -step returns and -returns, are commonly used to improve the sample efficiency of reinforcement learning (RL) methods. The variance of the multiste…