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Showing 151–200 of 677 papers

TitleStatusHype
FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control—0
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network—0
Collision- and Reachability-Aware Multi-Robot Control with Grounded LLM Planners—0
LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models—0
Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning—0
Cache-Efficient Posterior Sampling for Reinforcement Learning with LLM-Derived Priors Across Discrete and Continuous Domains—0
Offline Multi-agent Reinforcement Learning via Score Decomposition—0
Variational OOD State Correction for Offline Reinforcement Learning—0
Directly Forecasting Belief for Reinforcement Learning with DelaysCode0
Text-to-Decision Agent: Learning Generalist Policies from Natural Language Supervision—0
Learning Transferable Friction Models and LuGre Identification via Physics Informed Neural Networks—0
Adapting World Models with Latent-State Dynamics Residuals—0
Beyond Non-Expert Demonstrations: Outcome-Driven Action Constraint for Offline Reinforcement Learning—0
Handling Delay in Real-Time Reinforcement LearningCode0
Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent CooperationCode0
Adventurer: Exploration with BiGAN for Deep Reinforcement Learning—0
CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning—0
Likelihood Reward Redistribution—0
Application of linear regression method to the deep reinforcement learning in continuous action casesCode0
Residual Policy Gradient: A Reward View of KL-regularized Objective—0
SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning—0
AVG-DICE: Stationary Distribution Correction by Regression—0
Offline Reinforcement Learning via Inverse OptimizationCode0
RIZE: Regularized Imitation Learning via Distributional Reinforcement LearningCode0
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic—0
Yes, Q-learning Helps Offline In-Context RL—0
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement LearningCode0
On the Design of Safe Continual RL Methods for Control of Nonlinear SystemsCode0
CAMEL: Continuous Action Masking Enabled by Large Language Models for Reinforcement Learning—0
A Unifying Framework for Causal Imitation Learning with Hidden Confounders—0
Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning—0
Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning—0
Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution TasksCode0
IRIS: An Immersive Robot Interaction System—0
On Rollouts in Model-Based Reinforcement LearningCode0
Fat-to-Thin Policy Optimization: Offline RL with Sparse PoliciesCode0
TIMRL: A Novel Meta-Reinforcement Learning Framework for Non-Stationary and Multi-Task Environments—0
Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline DataCode0
An Empirical Study of Deep Reinforcement Learning in Continuing TasksCode0
SALE-Based Offline Reinforcement Learning with Ensemble Q-Networks—0
Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement LearningCode0
Hierarchical Subspaces of Policies for Continual Offline Reinforcement Learning—0
SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control TasksCode0
Active Reinforcement Learning Strategies for Offline Policy Improvement—0
RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors—0
Inverse Delayed Reinforcement Learning—0
Hierarchical Prompt Decision Transformer: Improving Few-Shot Policy Generalization with Global and Adaptive Guidance—0
Fast Convergence of Softmax Policy Mirror Ascent—0
Multi-Objective Algorithms for Learning Open-Ended Robotic Problems—0
Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration—0
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