Deep RL

BadRL: Sparse Targeted Backdoor Attack against Reinforcement Learning AAAI 2024 Balanced reward-inspired reinforcement learning for autonomous vehicle racing L4DC 2024 Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation AAAI 2024 Balancing Context Length and Mixing Times for Reinforcement Learning at Scale NeurIPS 2024 Behaviour Distillation ICLR 2024 BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images ICML 2024 Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations ICLR 2024 BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer (Student Abstract) AAAI 2024 Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms AAAI 2024 Beyond Optimism: Exploration With Partially Observable Rewards NeurIPS 2024 Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies ICLR 2024 Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control NeurIPS 2024 Bit_numeval at SemEval-2024 Task 7: Enhance Numerical Sensitivity and Reasoning Completeness for Quantitative Understanding SemEval 2024 Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge IJCAI 2024 Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays ICML 2024 Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents ICML 2024 Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds JMLR 2024 Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective CoRL 2024 Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning AAAI 2024 By Fair Means or Foul: Quantifying Collusion in a Market Simulation with Deep Reinforcement Learning IJCAI 2024 CACTO-SL: Using Sobolev learning to improve continuous actor-critic with trajectory optimization L4DC 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? NeurIPS 2024 Can You Rely on Synthetic Labellers in Preference-Based Reinforcement Learning? It’s Complicated AAAI 2024 Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning CVPR 2024 Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications AISTATS 2024