← Methods
Reinforcement Learning › Methods ›

Deep RL

3861 directly classified papers

Papers per year

Papers

Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions NIPS 2023
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization NIPS 2023
Weakly Coupled Deep Q-Networks NIPS 2023
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies NIPS 2023
Structured State Space Models for In-Context Reinforcement Learning NIPS 2023
$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning NIPS 2023
Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback NIPS 2023
TD Convergence: An Optimization Perspective NIPS 2023
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning NIPS 2023
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment NIPS 2023
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing NIPS 2023
Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift NIPS 2023
Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents NIPS 2023
Diversify \& Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement NIPS 2023
Task-aware world model learning with meta weighting via bi-level optimization NIPS 2023
Model-Free Active Exploration in Reinforcement Learning NIPS 2023
Self-Supervised Reinforcement Learning that Transfers using Random Features NIPS 2023
Latent exploration for Reinforcement Learning NIPS 2023
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning NIPS 2023
Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion NIPS 2023
General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence NIPS 2023
Bridging RL Theory and Practice with the Effective Horizon NIPS 2023
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training NIPS 2023
TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning NIPS 2023
Policy Gradient for Rectangular Robust Markov Decision Processes NIPS 2023