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Methodology
← Methods
Reinforcement Learning
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Methods
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Deep RL
3861 directly classified 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
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
NIPS 2020
Hierarchically Decoupled Imitation For Morphological Transfer
ICML 2020
Momentum-Based Policy Gradient Methods
ICML 2020
Learning to Ask Medical Questions using Reinforcement Learning
MLHC 2020
Deep Reinforcement Learning for Closed-Loop Blood Glucose Control
MLHC 2020
ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning
CORL 2020
Contrastive Variational Reinforcement Learning for Complex Observations
CORL 2020
Efficiently Solving MDPs with Stochastic Mirror Descent
ICML 2020
Constrained Markov Decision Processes via Backward Value Functions
ICML 2020
Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion
CORL 2020
Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous
CORL 2020
A Self-Tuning Actor-Critic Algorithm
NIPS 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
NIPS 2020
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning
NIPS 2020
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems
NIPS 2020
Production-based Cognitive Models as a Test Suite for Reinforcement Learning Algorithms
EMNLP 2020
Active Vision for Early Recognition of Human Actions
CVPR 2020
Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach
ICML 2020
Reinforced Curriculum Learning on Pre-Trained Neural Machine Translation Models
AAAI 2020
Reinforcement Learning with Dynamic Boltzmann Softmax Updates
IJCAI 2020
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent
IJCAI 2020
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise
COLT 2020
Provably efficient reinforcement learning with linear function approximation
COLT 2020
Root-n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank
COLT 2020
Noise Pollution in Hospital Readmission Prediction: Long Document Classification with Reinforcement Learning
ACL 2020
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