Browsing University of Waterloo by Subject "deep reinforcement learning"
Now showing items 1-4 of 4
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Asking for Help with a Cost in Reinforcement Learning
(University of Waterloo, 2020-05-15)Reinforcement learning (RL) is a powerful tool for developing intelligent agents, and the use of neural networks makes RL techniques more scalable to challenging real-world applications, from task-oriented dialogue systems ... -
Learning to Engage: An Application of Deep Reinforcement Learning in Living Architecture Systems
(University of Waterloo, 2023-05-30)Physical agents that can autonomously generate engaging, life-like behavior will lead to more responsive and interesting robots and other autonomous systems. Although many advances have been made for one-to-one interactions ... -
Learning-Free Methods for Goal Conditioned Reinforcement Learning from Images
(University of Waterloo, 2021-04-27)We are interested in training goal-conditioned reinforcement learning agents to reach arbitrary goals specified as images. In order to make our agent fully general, we provide the agent with only images of the environment ... -
PEV Charging Infrastructure Integration into Smart Grid
(University of Waterloo, 2020-05-05)Plug-in electric vehicles (PEVs) represent a huge step forward in a green transportation system, contribute to the reduction of greenhouse gas emission, and reduce the dependence on fossil fuel. With the increasing popularity ...