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Showing 251–300 of 677 papers

TitleStatusHype
DeepSafeMPC: Deep Learning-Based Model Predictive Control for Safe Multi-Agent Reinforcement Learning—0
A K-fold Method for Baseline Estimation in Policy Gradient Algorithms—0
Generalized Hidden Parameter MDPs Transferable Model-based RL in a Handful of Trials—0
Generalized Maximum Entropy Reinforcement Learning via Reward Shaping—0
Accelerating Inverse Reinforcement Learning with Expert Bootstrapping—0
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning—0
Learning Constraint Network from Demonstrations via Positive-Unlabeled Learning with Memory Replay—0
Deep Reinforcement Learning for Dexterous Manipulation with Concept Networks—0
Balancing Constraints and Rewards with Meta-Gradient D4PG—0
Deep exploration by novelty-pursuit with maximum state entropy—0
Aggressive Q-Learning with Ensembles: Achieving Both High Sample Efficiency and High Asymptotic Performance—0
Decorrelated Double Q-learning—0
Adapting Double Q-Learning for Continuous Reinforcement Learning—0
AgentMixer: Multi-Agent Correlated Policy Factorization—0
SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning—0
Learn a Prior for RHEA for Better Online Planning—0
Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies—0
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning—0
Backward Imitation and Forward Reinforcement Learning via Bi-directional Model Rollouts—0
Data Valuation for Offline Reinforcement Learning—0
A Generalized Training Approach for Multiagent Learning—0
A Game-Theoretic Perspective of Generalization in Reinforcement Learning—0
AVG-DICE: Stationary Distribution Correction by Regression—0
CrossNorm: On Normalization for Off-Policy Reinforcement Learning—0
Average-Reward Reinforcement Learning with Trust Region Methods—0
Accelerating Diffusion Models in Offline RL via Reward-Aware Consistency Trajectory Distillation—0
Latent Space Energy-based Neural ODEs—0
Learning Complicated Manipulation Skills via Deterministic Policy with Limited Demonstrations—0
Learning Intrinsic Symbolic Rewards in Reinforcement Learning—0
Cross-Domain Imitation Learning with a Dual Structure—0
Cooperative Multi-Agent Deep Reinforcement Learning in Content Ranking Optimization—0
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization—0
Cooperative Heterogeneous Deep Reinforcement Learning—0
Auto-Encoding Inverse Reinforcement Learning—0
Control Transformer: Robot Navigation in Unknown Environments through PRM-Guided Return-Conditioned Sequence Modeling—0
AutoDIME: Automatic Design of Interesting Multi-Agent Environments—0
Active Reinforcement Learning Strategies for Offline Policy Improvement—0
A Unifying Framework for Causal Imitation Learning with Hidden Confounders—0
Actor-Director-Critic: A Novel Deep Reinforcement Learning Framework—0
Keyframe-Focused Visual Imitation Learning—0
Continuous Neural Algorithmic Planners—0
Continuous Mean-Zero Disagreement-Regularized Imitation Learning (CMZ-DRIL)—0
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment—0
Improving Context-Based Meta-Reinforcement Learning with Self-Supervised Trajectory Contrastive Learning—0
Improving Actor-Critic Reinforcement Learning via Hamiltonian Monte Carlo Method—0
Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization—0
Improved Soft Actor-Critic: Mixing Prioritized Off-Policy Samples with On-Policy Experience—0
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates—0
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning—0
Adversarial Imitation Learning via Random Search—0
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