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

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Showing 9326–9350 of 15113 papers

TitleStatusHype
Quantile-Based Policy Optimization for Reinforcement Learning—0
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping—0
Quantile Reinforcement Learning—0
Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation—0
Quantitative Day Trading from Natural Language using Reinforcement Learning—0
Quantitative Resilience Modeling for Autonomous Cyber Defense—0
Quantitative Trading using Deep Q Learning—0
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning—0
Quantum algorithms applied to satellite mission planning for Earth observation—0
Quantum Architecture Search via Continual Reinforcement Learning—0
Quantum Compiling with Reinforcement Learning on a Superconducting Processor—0
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning—0
Quantum Control based on Deep Reinforcement Learning—0
Quantum deep recurrent reinforcement learning—0
Quantum-enhanced machine learning—0
Quantum-Enhanced Reinforcement Learning for Power Grid Security Assessment—0
Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory search—0
Quantum Logic Gate Synthesis as a Markov Decision Process—0
Quantum machine learning with glow for episodic tasks and decision games—0
Quantum Multi-Agent Meta Reinforcement Learning—0
Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets—0
Quantum policy gradient algorithms—0
Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learning—0
Quantum reinforcement learning in continuous action space—0
Quantum Reinforcement Learning via Policy Iteration—0
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Benchmark Results

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