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Reinforcement Learning
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Methods
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Deep RL
3,861 papers
Papers per year
2005: 1
2006: 9
2007: 14
2008: 15
2009: 9
2010: 21
2011: 27
2012: 32
2013: 21
2014: 17
2015: 10
2016: 33
2017: 102
2018: 222
2019: 399
2020: 450
2021: 533
2022: 478
2023: 532
2024: 513
2025: 326
2026: 97
Papers
Contrastive Reinforcement Learning of Symbolic Reasoning Domains
NIPS 2021
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic
NIPS 2021
Learning Diverse Policies in MOBA Games via Macro-Goals
NIPS 2021
Neural optimal feedback control with local learning rules
NIPS 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting
NIPS 2021
Dynamic Bottleneck for Robust Self-Supervised Exploration
NIPS 2021
Risk-Aware Transfer in Reinforcement Learning using Successor Features
NIPS 2021
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks
NIPS 2021
Regret Minimization Experience Replay in Off-Policy Reinforcement Learning
NIPS 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
NIPS 2021
Reinforcement learning for optimization of variational quantum circuit architectures
NIPS 2021
Behavior From the Void: Unsupervised Active Pre-Training
NIPS 2021
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
NIPS 2021
Monte Carlo Tree Search With Iteratively Refining State Abstractions
NIPS 2021
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations
NIPS 2021
Functional Regularization for Reinforcement Learning via Learned Fourier Features
NIPS 2021
Agent Modelling under Partial Observability for Deep Reinforcement Learning
NIPS 2021
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning
NIPS 2021
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data
NIPS 2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
NIPS 2021
Hierarchical Reinforcement Learning with Timed Subgoals
NIPS 2021
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives
NIPS 2021
Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation
NIPS 2021
Reinforcement Learning in Newcomblike Environments
NIPS 2021
Reinforcement Learning with Latent Flow
NIPS 2021
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