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Shared Autonomy via Deep Reinforcement Learning
TLDR
We propose a deep reinforcement learning framework for model-free shared autonomy that lifts these assumptions. Expand
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SQIL: Imitation Learning via Regularized Behavioral Cloning
TLDR
We propose combining the standard maximum-likelihood objective of BC, which encourages the agent to imitate the expert in demonstrated states, with a penalty on the soft Bellman error of the soft Q function. Expand
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SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards
TLDR
We propose a simple alternative that still uses RL, but does not require learning a reward function, and achieves competitive results compared to GAIL on a variety of image-based and low-dimensional tasks. Expand
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Impact of Statin Use After Heart Transplantation: A Meta-Analysis
Background—Although various studies revealed the beneficial effects of statins in post–cardiac transplant patients, these were relatively small and low-powered studies. We performed a meta-analysisExpand
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Learning Human Objectives by Evaluating Hypothetical Behavior
TLDR
We propose an algorithm that safely and interactively learns a model of the user's reward function in a reinforcement learning setting with unknown dynamics, an unknown reward function, and unknown unsafe states. Expand
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Scaled Autonomy: Enabling Human Operators to Control Robot Fleets
TLDR
Autonomous robots often encounter challenging situations where their control policies fail and an expert human operator must briefly intervene, e.g., through teleoperation. Expand
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HIBERNATING MYOCARDIUM AS A CAUSE OF RECURRENT VENTRICULAR TACHYCARDIA - UTILITY OF FDG-PET IMAGING
Viability imaging with FDG-PET has the unique ability to differentiate between scar and hibernating myocardium and is typically used to guide revascularization strategies. We present a case ofExpand
What makes a game sell
Even though video gaming industry has experienced a continuous growth over the past years stepping into mass market and becoming a part of mass media culture, lately it has faced a totalExpand