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Contributed talk: Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning
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  • title: Contributed talk: Adversarial Policies: Attacking Deep Reinforcement Learning
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            Contributed talk: Adversarial Policies: Attacking Deep Reinforcement Learning
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            Contributed talk: Adversarial Policies: Attacking Deep Reinforcement Learning

            Dec 14, 2019

            Speakers

            AG

            Adam Gleave

            Speaker · 2 followers

            About

            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…

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            NIPS 2019

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            Category · 10.8k presentations

            About NIPS 2019

            Neural Information Processing Systems (NeurIPS) is a multi-track machine learning and computational neuroscience conference that includes invited talks, demonstrations, symposia and oral and poster presentations of refereed papers. Following the conference, there are workshops which provide a less formal setting.

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