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Showing 451–500 of 677 papers

TitleStatusHype
Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity—0
Small Dataset, Big Gains: Enhancing Reinforcement Learning by Offline Pre-Training with Model Based Augmentation—0
Smooth Imitation Learning via Smooth Costs and Smooth Policies—0
SOAC: The Soft Option Actor-Critic Architecture—0
Soft Actor-Critic Algorithm with Truly-satisfied Inequality Constraint—0
SoftDICE for Imitation Learning: Rethinking Off-policy Distribution Matching—0
Soft policy optimization using dual-track advantage estimator—0
Solving Minimum-Cost Reach Avoid using Reinforcement Learning—0
SparseDice: Imitation Learning for Temporally Sparse Data via Regularization—0
SPP-RL: State Planning Policy Reinforcement Learning—0
Stabilizing Off-Policy Reinforcement Learning with Conservative Policy Gradients—0
Multiagent Model-based Credit Assignment for Continuous Control—0
Stochastic Variance Reduction for Policy Gradient Estimation—0
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees—0
Supported Trust Region Optimization for Offline Reinforcement Learning—0
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network—0
Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning—0
Temporal Abstraction in Reinforcement Learning with Offline Data—0
Temporal-adaptive Hierarchical Reinforcement Learning—0
MinMaxMin Q-learning—0
SQT -- std Q-target—0
Text-to-Decision Agent: Learning Generalist Policies from Natural Language Supervision—0
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning—0
The Exploration-Exploitation Dilemma Revisited: An Entropy Perspective—0
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously—0
The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting—0
Theoretically Guaranteed Policy Improvement Distilled from Model-Based Planning—0
Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation—0
Mind the Model, Not the Agent: The Primacy Bias in Model-based RL—0
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking—0
TIMRL: A Novel Meta-Reinforcement Learning Framework for Non-Stationary and Multi-Task Environments—0
TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching—0
STOPS: Short-Term-based Volatility-controlled Policy Search and its Global Convergence—0
Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control—0
Towards Characterizing Divergence in Deep Q-Learning—0
Towards Simplicity in Deep Reinforcement Learning: Streamlined Off-Policy Learning—0
Transferable Reward Learning by Dynamics-Agnostic Discriminator Ensemble—0
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning—0
Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound—0
Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning—0
Understanding the Asymptotic Performance of Model-Based RL Methods—0
Unified Policy Optimization for Continuous-action Reinforcement Learning in Non-stationary Tasks and Games—0
Universal Successor Features for Transfer Reinforcement Learning—0
Unsupervised Discovery of Continuous Skills on a Sphere—0
User-Oriented Robust Reinforcement Learning—0
Value Improved Actor Critic Algorithms—0
Value Summation: A Novel Scoring Function for MPC-based Model-based Reinforcement Learning—0
Variance Reduction for Reinforcement Learning in Input-Driven Environments—0
Variational OOD State Correction for Offline Reinforcement Learning—0
V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects—0
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