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 8026–8050 of 15113 papers

TitleStatusHype
Optimization of anemia treatment in hemodialysis patients via reinforcement learning—0
Optimization of Image Transmission in a Cooperative Semantic Communication Networks—0
Optimization of Multi-Factor Model in Quantitative Trading Based On Reinforcement Learning—0
Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning—0
Optimization on a Budget: A Reinforcement Learning Approach—0
Optimization Solution Functions as Deterministic Policies for Offline Reinforcement Learning—0
Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning—0
Optimized cost function for demand response coordination of multiple EV charging stations using reinforcement learning—0
Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning—0
Optimizing AD Pruning of Sponsored Search with Reinforcement Learning—0
Optimizing Age of Information Through Aerial Reconfigurable Intelligent Surfaces: A Deep Reinforcement Learning Approach—0
Optimizing Airborne Wind Energy with Reinforcement Learning—0
Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspective—0
Optimizing Automatic Differentiation with Deep Reinforcement Learning—0
Optimizing Autonomous Driving for Safety: A Human-Centric Approach with LLM-Enhanced RLHF—0
Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning—0
Optimizing Coverage and Capacity in Cellular Networks using Machine Learning—0
Optimizing Crop Management with Reinforcement Learning and Imitation Learning—0
Optimizing Cyber Defense in Dynamic Active Directories through Reinforcement Learning—0
Optimizing Data Collection in Deep Reinforcement Learning—0
Optimizing Downlink C-NOMA Transmission with Movable Antennas: A DDPG-based Approach—0
Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks—0
Optimizing Fantasy Sports Team Selection with Deep Reinforcement Learning—0
Optimizing Gene-Based Testing for Antibiotic Resistance Prediction—0
Optimizing human-interpretable dialog management policy using Genetic Algorithm—0
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Benchmark Results

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