Who Cited It

Asynchronous Methods for Deep Reinforcement Learning

2016 · arXiv (Cornell University) · 1,689 citations · 8 from inside this corpus

Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu

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Asynchronous Methods for Deep Reinforcement Learning (2016)Asynchronous Methods for Deep…Long Short-Term Memory (1997)Long Short-Term MemoryAdam: A Method for Stochastic Optimization (2014)Adam: A Method for Stochastic…Reinforcement Learning: An Introduction (2005)Reinforcement Learning: An In…Adaptive Subgradient Methods for Online Learning and Stochastic Optimization (2010)Adaptive Subgradient Methods …Simple statistical gradient-following algorithms for connectionist reinforcement learning (1992)Simple statistical gradient-f…ADADELTA: An Adaptive Learning Rate Method (2012)ADADELTA: An Adaptive Learnin…Continuous control with deep reinforcement learning (2015)Continuous control with deep …Playing Atari with Deep Reinforcement Learning (2013)Playing Atari with Deep Reinf…High-Dimensional Continuous Control Using Generalized Advantage Estimation (2015)High-Dimensional Continuous C…End-to-End Training of Deep Visuomotor Policies (2015)End-to-End Training of Deep V…Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short … (2017)Diagnosing Non-Intermittent A…Mastering the game of Go without human knowledge (2017)Mastering the game of Go with…Grandmaster level in StarCraft II using multi-agent reinforcement learning (2019)Grandmaster level in StarCraf…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…Sigmoid-weighted linear units for neural network function approximation in reinforcement … (2018)Sigmoid-weighted linear units…Rainbow: Combining Improvements in Deep Reinforcement Learning (2018)Rainbow: Combining Improvemen…A State-of-the-Art Survey on Deep Learning Theory and Architectures (2019)A State-of-the-Art Survey on …Deep Reinforcement Learning That Matters (2018)Deep Reinforcement Learning T…
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Topics

Reinforcement Learning in RoboticsComputer Science
Advanced Memory and Neural ComputingEngineering
Domain Adaptation and Few-Shot LearningComputer Science

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complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports8 author record(s) attached.
  • supports32 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:56+00:00.

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