Who Cited It

Deep Reinforcement Learning with Double Q-Learning

2016 · Proceedings of the AAAI Conference on Artificial Intelligence · 3,516 citations · 8 from inside this corpus

Hado van Hasselt, Arthur Guez, David Silver

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Deep Reinforcement Learning with Double Q-Learning (2016)Deep Reinforcement Learning w…Reinforcement Learning: A Survey (1996)Reinforcement Learning: A Sur…Introduction to Reinforcement Learning (1998)Introduction to Reinforcement…Learning from Delayed Rewards (1989)Learning from Delayed RewardsLearning to Predict by the Methods of Temporal Differences (1988)Learning to Predict by the Me…Learning to predict by the methods of temporal differences (1988)Learning to predict by the me…Self-improving reactive agents based on reinforcement learning, planning and teaching (1992)Self-improving reactive agent…Temporal difference learning and TD-Gammon (1995)Temporal difference learning …Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dyna… (1990)Integrated Architectures for …Overcoming catastrophic forgetting in neural networks (2017)Overcoming catastrophic forge…Deep Reinforcement Learning: A Brief Survey (2017)Deep Reinforcement Learning: …Federated Learning in Mobile Edge Networks: A Comprehensive Survey (2020)Federated Learning in Mobile …Addressing Function Approximation Error in Actor-Critic Methods (2018)Addressing Function Approxima…A Roadmap of Agent Research and Development (1998)A Roadmap of Agent Research a…Dueling Network Architectures for Deep Reinforcement Learning (2015)Dueling Network Architectures…Rainbow: Combining Improvements in Deep Reinforcement Learning (2018)Rainbow: Combining Improvemen…Federated Learning for Healthcare Informatics (2020)Federated Learning for Health…
16 of 16 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Reinforcement Learning: A Survey19968,953
Introduction to Reinforcement Learning19986,917
Learning from Delayed Rewards19895,473
Learning to Predict by the Methods of Temporal Differences19883,970
Learning to predict by the methods of temporal differences19882,818
Self-improving reactive agents based on reinforcement learning, planning and teaching19921,656
Temporal difference learning and TD-Gammon19951,493
Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dyna…19901,375

What cites it, inside the corpus

PaperYearCited
Overcoming catastrophic forgetting in neural networks20177,624
Deep Reinforcement Learning: A Brief Survey20174,434
Federated Learning in Mobile Edge Networks: A Comprehensive Survey20202,538
Addressing Function Approximation Error in Actor-Critic Methods20182,372
A Roadmap of Agent Research and Development19982,099
Dueling Network Architectures for Deep Reinforcement Learning20151,811
Rainbow: Combining Improvements in Deep Reinforcement Learning20181,783
Federated Learning for Healthcare Informatics20201,497

Links

DOI · Open access copy · OpenAlex record

Topics

Reinforcement Learning in RoboticsComputer Science
Evolutionary Algorithms and ApplicationsComputer Science
Adversarial Robustness in Machine LearningComputer Science

Is this record sound?

complete

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

  • supports3 author record(s) attached.
  • supports34 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 2026-09-04T03:58:46+00:00.

sha256 bba2969b3567609a…