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Showing 351–375 of 677 papers

TitleStatusHype
The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting—0
Meta-Reinforcement Learning via Exploratory Task Clustering—0
CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning—0
Sample Dropout: A Simple yet Effective Variance Reduction Technique in Deep Policy OptimizationCode0
Online Reinforcement Learning in Non-Stationary Context-Driven EnvironmentsCode0
Bridging Physics-Informed Neural Networks with Reinforcement Learning: Hamilton-Jacobi-Bellman Proximal Policy Optimization (HJBPPO)—0
Neural Episodic Control with State Abstraction—0
Which Experiences Are Influential for Your Agent? Policy Iteration with Turn-over DropoutCode0
Certifiably Robust Reinforcement Learning through Model-Based Abstract Interpretation—0
Actor-Director-Critic: A Novel Deep Reinforcement Learning Framework—0
Genetic Imitation Learning by Reward Extrapolation—0
Contextual Conservative Q-Learning for Offline Reinforcement Learning—0
Pontryagin Optimal Control via Neural NetworksCode0
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces—0
Offline Robot Reinforcement Learning with Uncertainty-Guided Human Expert Sampling—0
Off-Policy Deep Reinforcement Learning Algorithms for Handling Various Robotic Manipulator Tasks—0
Accelerating Self-Imitation Learning from Demonstrations via Policy Constraints and Q-Ensemble—0
First Go, then Post-Explore: the Benefits of Post-Exploration in Intrinsic Motivation—0
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed DatasetsCode0
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking—0
Continuous Neural Algorithmic Planners—0
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning—0
On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement LearningCode0
Contextual Transformer for Offline Meta Reinforcement Learning—0
Out-of-Dynamics Imitation Learning from Multimodal DemonstrationsCode0
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