SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9576–9600 of 15113 papers

TitleStatusHype
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning—0
Policy Mirror Descent for Reinforcement Learning: Linear Convergence, New Sampling Complexity, and Generalized Problem Classes—0
Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm—0
Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning—0
Meta-Reinforcement Learning for Reliable Communication in THz/VLC Wireless VR NetworksCode0
Scalable Voltage Control using Structure-Driven Hierarchical Deep Reinforcement Learning—0
Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep LearningCode0
Reinforcement Learning for Freight Booking Control Problems—0
Learning-based vs Model-free Adaptive Control of a MAV under Wind Gust—0
Challenges for Using Impact Regularizers to Avoid Negative Side Effects—0
CoordiQ : Coordinated Q-learning for Electric Vehicle Charging Recommendation—0
Exploring the Impact of Tunable Agents in Sequential Social DilemmasCode0
Universal Trading for Order Execution with Oracle Policy Distillation—0
Reinforcement Learning based Per-antenna Discrete Power Control for Massive MIMO Systems—0
Safe Multi-Agent Reinforcement Learning via Shielding—0
Reinforcement Learning Assisted Beamforming for Inter-cell Interference Mitigation in 5G Massive MIMO Networks—0
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning—0
Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challenges—0
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors—0
Data sharing gamesCode0
ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning—0
Channel Estimation via Successive Denoising in MIMO OFDM Systems: A Reinforcement Learning Approach—0
Fast Sequence Generation with Multi-Agent Reinforcement Learning—0
GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning—0
Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified