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Distributional Successor Features Enable Zero-Shot Policy Optimization
Intelligent agents must be generalists, capable of quickly adapting to various tasks.
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Bayesian Adaptive Calibration and Optimal Design
BACON allows computational resources to be focused on simulations that provide the most value in terms of reducing epistemic uncertainty.
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Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
Ben Eysenbach, Russ R. Salakhutdinov, Sergey Levine
The history of learning for control has been an exciting back and forth between twobroad classes ofalgorithms: planning andreinforcement learning.
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A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation
Runzhe Yang, Xingyuan Sun, Karthik Narasimhan
Neural Information Processing Systems http://nips.cc/
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UnpackingRewardShaping
Much of this work is based on upper confidence bound (UCB) principles and prescribes some kind of exploration bonus to prioritize exploration of rarely visited regions.
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