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Methodology
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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
FactorSim: Generative Simulation via Factorized Representation
NIPS 2024
EnMatch: Matchmaking for Better Player Engagement via Neural Combinatorial Optimization
AAAI 2024
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning
NIPS 2024
VLMPC: Vision-Language Model Predictive Control for Robotic Manipulation
RSS 2024
LogoStyleFool: Vitiating Video Recognition Systems via Logo Style Transfer
AAAI 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property
AAAI 2024
Proofread: Fixes All Errors with One Tap
ACL 2024
Imitation Bootstrapped Reinforcement Learning
RSS 2024
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
NIPS 2024
Online Learning with Off-Policy Feedback in Adversarial MDPs
IJCAI 2024
Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration
NIPS 2024
Global Optimality of Single-Timescale Actor-Critic under Continuous State-Action Space: A Study on Linear Quadratic Regulator
IJCAI 2024
ReCoRe: Regularized Contrastive Representation Learning of World Model
CVPR 2024
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
NIPS 2024
Versatile Navigation Under Partial Observability via Value-guided Diffusion Policy
CVPR 2024
The surprising efficiency of temporal difference learning for rare event prediction
NIPS 2024
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
COLT 2024
Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
NIPS 2024
Scale-free Adversarial Reinforcement Learning
COLT 2024
Settling the sample complexity of online reinforcement learning
COLT 2024
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL
NIPS 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions
COLT 2024
Exploration by Learning Diverse Skills through Successor State Representations
NIPS 2024
Learning to Control Camera Exposure via Reinforcement Learning
CVPR 2024
NeoRL: Efficient Exploration for Nonepisodic RL
NIPS 2024
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