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Sat Dec 14 08:00 AM -- 07:00 PM (PST) @ West Exhibition Hall C
Deep Reinforcement Learning
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Joshua Achiam · Carlos Florensa · Christopher Grimm · Haoran Tang · Vivek Veeriah

Workshop Home Page

In recent years, the use of deep neural networks as function approximators has enabled researchers to extend reinforcement learning techniques to solve increasingly complex control tasks. The emerging field of deep reinforcement learning has led to remarkable empirical results in rich and varied domains like robotics, strategy games, and multiagent interaction. This workshop will bring together researchers working at the intersection of deep learning and reinforcement learning, and it will help interested researchers outside of the field gain a high-level view about the current state of the art and potential directions for future contributions.

Welcome Comments (Talk)
Grandmaster Level in StarCraft II using Multi-Agent Reinforcement Learning - Invited Talk (Talk)
Contributed Talks (Talk)
Bayes-Adaptive Deep Reinforcement Learning via Meta-Learning - Invited Talk (Talk)
Coffee Break (Break)
Optico: A Framework for Model-Based Optimization with MuJoCo Physics - Invited Talk (Talk)
Contributed Talks (Talk)
Late-Breaking Papers (Talks) (Talk)
Invited Talk (Talk)
Contributed Talks (Talk)
Poster Session
NeurIPS RL Competitions Results Presentations (Demonstration)
Assessing the Robustness of Deep RL Algorithms - Invited Talk (Talk)
Panel Discussion (Panel)