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Deep RL

3861 directly classified papers

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Papers

Bit_numeval at SemEval-2024 Task 7: Enhance Numerical Sensitivity and Reasoning Completeness for Quantitative Understanding SEMEVAL 2024
CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems AAAI 2024
Exploring Gradient Explosion in Generative Adversarial Imitation Learning: A Probabilistic Perspective AAAI 2024
VLMPC: Vision-Language Model Predictive Control for Robotic Manipulation RSS 2024
EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning EACL 2024
Optimal Attack and Defense for Reinforcement Learning AAAI 2024
Improve Robustness of Reinforcement Learning against Observation Perturbations via l∞ Lipschitz Policy Networks AAAI 2024
Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning AAAI 2024
OCEAN-MBRL: Offline Conservative Exploration for Model-Based Offline Reinforcement Learning AAAI 2024
Finding a Needle in the Adversarial Haystack: A Targeted Paraphrasing Approach For Uncovering Edge Cases with Minimal Distribution Distortion EACL 2024
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning COLT 2024
ERL-TD: Evolutionary Reinforcement Learning Enhanced with Truncated Variance and Distillation Mutation AAAI 2024
Episodic Return Decomposition by Difference of Implicitly Assigned Sub-trajectory Reward AAAI 2024
Settling the sample complexity of online reinforcement learning COLT 2024
Scale-free Adversarial Reinforcement Learning COLT 2024
Exploration via linearly perturbed loss minimisation AISTATS 2024
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments AAAI 2024
Watch Every Step! LLM Agent Learning via Iterative Step-level Process Refinement EMNLP 2024
Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems AISTATS 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024
Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs COLT 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions COLT 2024
On learning history-based policies for controlling Markov decision processes AISTATS 2024
Model-based Policy Optimization under Approximate Bayesian Inference AISTATS 2024
Learning Uncertainty-Aware Temporally-Extended Actions AAAI 2024