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Reinforcement Learning

2932 directly classified papers

Papers per year

Papers

Sustainability of Data Center Digital Twins with Reinforcement Learning AAAI 2024
Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning NIPS 2024
MANDREL: Modular Reinforcement Learning Pipelines for Material Discovery AAAI 2024
Stage-Aware Learning for Dynamic Treatments JMLR 2024
Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation NIPS 2024
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning NIPS 2024
State Chrono Representation for Enhancing Generalization in Reinforcement Learning NIPS 2024
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach JMLR 2024
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning JMLR 2024
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces NIPS 2024
Pearl: A Production-Ready Reinforcement Learning Agent JMLR 2024
Risk-sensitive control as inference with Rényi divergence NIPS 2024
NeoRL: Efficient Exploration for Nonepisodic RL NIPS 2024
Learning Regularized Graphon Mean-Field Games with Unknown Graphons JMLR 2024
Reward (Mis)design for Autonomous Driving (Abstract Reprint) AAAI 2024
Decentralized Natural Policy Gradient with Variance Reduction for Collaborative Multi-Agent Reinforcement Learning JMLR 2024
Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning JMLR 2024
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity JMLR 2024
BenchMARL: Benchmarking Multi-Agent Reinforcement Learning JMLR 2024
Active Reinforcement Learning for Robust Building Control AAAI 2024
Exploration by Learning Diverse Skills through Successor State Representations NIPS 2024
On Divergence Measures for Training GFlowNets NIPS 2024
Thompson Sampling Itself is Differentially Private AISTATS 2024
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds JMLR 2024
Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility AAAI 2024