Deep residual reinforcement learning

Deep residual reinforcement learning

<p>We revisit residual algorithms in both model-free and model-based reinforcement learning settings. We propose the bidirectional target network technique to stabilize residual algorithms, yielding a residual version of DDPG that significantly outperforms vanilla DDPG in the DeepMind Control...

Full description

Bibliographic Details
Main Authors:	Zhang, S, Boehmer, W, Whiteson, S
Format:	Conference item
Language:	English
Published:	International Foundation for Autonomous Agents and Multiagent Systems 2020

Similar Items

Transient non−stationarity and generalisation in deep reinforcement learning
by: Igl, M, et al.
Published: (2021)

Deep coordination graphs
by: Boehmer, W, et al.
Published: (2020)

Bayesian action decoder for deep multi-agent reinforcement learning
by: Whiteson, S
Published: (2019)

UneVEn: Universal value exploration for multi-agent reinforcement learning
by: Gupta, T, et al.
Published: (2021)

Deep variational reinforcement learning for POMDPs
by: Igl, M, et al.
Published: (2018)

Learning to communicate with Deep multi-agent reinforcement learning
by: Foerster, J, et al.
Published: (2016)

Multi-agent common knowledge reinforcement learning
by: de Witt, C, et al.
Published: (2019)

Randomized entity-wise factorization for multi-agent reinforcement learning
by: Iqbal, S, et al.
Published: (2021)

Learning retrospective knowledge with reverse reinforcement learning
by: Zhang, S, et al.
Published: (2020)

TreeQN and ATreeC: differentiable tree planning for deep reinforcement learning
by: Farquhar, G, et al.
Published: (2018)

Stabilising experience replay for deep multi-agent reinforcement learning
by: Foerster, J, et al.
Published: (2017)

Deep reinforcement learning to multi-agent deep reinforcement learning
by: Samieiyeganeh, Mehdi, et al.
Published: (2022)

Generalized Off-Policy Actor-Critic
by: Zhang, S, et al.
Published: (2019)

Monotonic value function factorisation for deep multi-agent reinforcement learning
by: Rashid, T, et al.
Published: (2020)

Weighted QMIX: Expanding monotonic value function factorisation for deep multi−agent reinforcement learning
by: Rashid, T, et al.
Published: (2020)

QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning
by: Rashid, T, et al.
Published: (2018)

OFFER: Off-environment reinforcement learning
by: Ciosek, K, et al.
Published: (2017)

Mean−variance policy iteration for risk−averse reinforcement learning
by: Zhang, S, et al.
Published: (2021)

Meta-learning for deep reinforcement learning
by: Poon, Jun Yaw
Published: (2021)

Deep-attack over the deep reinforcement learning
by: Li, Yang, et al.
Published: (2022)

Deep Reinforcement Learning For Control
by: Bakar, Nurul Asyikin Abu
Published: (2021)

Watermarking deep reinforcement learning
by: Sim, Ming Jie
Published: (2021)

Expected policy gradients for reinforcement learning
by: Ciosek, K, et al.
Published: (2020)

Inverse reinforcement learning from failure
by: Shiarlis, K, et al.
Published: (2016)

Continuous control for robot based on deep reinforcement learning
by: Zhang, Shansi
Published: (2019)

Deep reinforcement learning for intractable routing & inverse problems
by: Zhang, Rongkai
Published: (2023)

Fingerprint policy optimisation for robust reinforcement learning
by: Paul, S, et al.
Published: (2019)

Learn to steer through deep reinforcement learning
by: Wu, Keyu, et al.
Published: (2019)

Understanding representation learning for deep reinforcement learning
by: Le Lan, C
Published: (2023)

Adversarial robustness of deep reinforcement learning
by: Qu, Xinghua
Published: (2022)

Deep reinforcement learning for inventory management
by: Rishab, Aryan
Published: (2022)

Deep Reinforcement Learning in complex environments
by: Nardelli, N
Published: (2021)

Deep multi-agent reinforcement learning
by: Foerster, J
Published: (2018)

VariBAD: variational bayes-adaptive deep RL via meta-learning
by: Whiteson, S
Published: (2021)

Deep reinforcement learning with robust deep deterministic policy gradient
by: Teckchai Tiong, et al.
Published: (2020)

Enzyme catalytic residue prediction using deep learning methods
by: Guan, Jia Sheng
Published: (2023)

Deep learning and reinforcement learning for trading financial assets
by: Mundhra, Divyesh
Published: (2022)

Learning manipulation skills using deep reinforcement learning
by: Tan, Herman Jin Xing
Published: (2021)

VIREL: A variational inference framework for reinforcement learning
by: Fellows, M, et al.
Published: (2019)

Efficient and scalable methods for deep reinforcement learning
by: Farquhar, G
Published: (2020)