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Deep RL

3861 directly classified papers

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Papers

Multi-Agent Reinforcement Learning with Reward Delays L4DC 2023
Practical Critic Gradient based Actor Critic for On-Policy Reinforcement Learning L4DC 2023
Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching L4DC 2023
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion L4DC 2023
Safe and Efficient Reinforcement Learning using Disturbance-Observer-Based Control Barrier Functions L4DC 2023
ISAACS: Iterative Soft Adversarial Actor-Critic for Safety L4DC 2023
Faster Target Encirclement with Utilization of Obstacles via Multi-Agent Reinforcement Learning ACML 2023
Roll-Drop: accounting for observation noise with a single parameter L4DC 2023
Agile Catching with Whole-Body MPC and Blackbox Policy Learning L4DC 2023
CT-DQN: Control-Tutored Deep Reinforcement Learning L4DC 2023
Warm-Start Actor-Critic: From Approximation Error to Sub-optimality Gap ICML 2023
Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data ICML 2023
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation ICML 2023
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments ICML 2023
Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning ICML 2023
Model-Based Reinforcement Learning for Cavity Filter Tuning L4DC 2023
Hyperparameter Tuning of an Off-Policy Reinforcement Learning Algorithm for H∞ Tracking Control L4DC 2023
Krylov–Bellman boosting: Super-linear policy evaluation in general state spaces AISTATS 2023
Token Turing Machines CVPR 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes ICML 2023
MRRL: Modifying the Reference via Reinforcement Learning for Non-Autoregressive Joint Multiple Intent Detection and Slot Filling EMNLP 2023
Provable Safe Reinforcement Learning with Binary Feedback AISTATS 2023
Uniformly Conservative Exploration in Reinforcement Learning AISTATS 2023
Near-Optimal Differentially Private Reinforcement Learning AISTATS 2023
Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning AISTATS 2023