11 citations · 18 across the 8 of their papers we have counts for
4 papers · 1 filter
Simplified Temporal Consistency Reinforcement Learning
Yi Zhao, Wenshuai Zhao, Rinu Boney +2
Reinforcement learning is able to solve complex sequential decision-making tasks but is currently limited by sample efficiency and required computation. To improve sample efficienc…
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
Yi Zhao, Rinu Boney, Alexander Ilin +2
Offline reinforcement learning, by learning from a fixed dataset, makes it possible to learn agent behaviors without interacting with the environment. However, depending on the qua…
Regularizing Model-Based Planning with Energy-Based Models
Rinu Boney, Juho Kannala, Alexander Ilin
Model-based reinforcement learning could enable sample-efficient learning by quickly acquiring rich knowledge about the world and using it to improve behaviour without additional d…
Regularizing Trajectory Optimization with Denoising Autoencoders
Rinu Boney, Norman Di Palo, Mathias Berglund +4
Trajectory optimization using a learned model of the environment is one of the core elements of model-based reinforcement learning. This procedure often suffers from exploiting ina…