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 5176–5200 of 15113 papers

TitleStatusHype
Hybrid Information-driven Multi-agent Reinforcement Learning—0
Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization—0
Hybrid Learning for Orchestrating Deep Learning Inference in Multi-user Edge-cloud Networks—0
Hybrid Learning with New Value Function for the Maximum Common Subgraph Problem—0
Hybrid Policies Using Inverse Rewards for Reinforcement Learning—0
Hybrid Q-Learning Applied to Ubiquitous recommender system—0
Hybrid Reinforcement Learning and Model Predictive Control for Adaptive Control of Hydrogen-Diesel Dual-Fuel Combustion—0
Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections—0
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs—0
Hybrid Reinforcement Learning for Optimizing Pump Sustainability in Real-World Water Distribution Networks—0
Hybrid Reinforcement Learning for STAR-RISs: A Coupled Phase-Shift Model Based Beamformer—0
Hybrid Reinforcement Learning Framework for Mixed-Variable Problems—0
Hybrid Reinforcement Learning from Offline Observation Alone—0
Hybrid Supervised and Reinforcement Learning for the Design and Optimization of Nanophotonic Structures—0
Hybrid Systems Neural Control with Region-of-Attraction Planner—0
Mixed Traffic Control and Coordination from Pixels—0
Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation—0
Hybrid UAV-enabled Secure Offloading via Deep Reinforcement Learning—0
Hybrid Value Estimation for Off-policy Evaluation and Offline Reinforcement Learning—0
Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning—0
Hyperbolically-Discounted Reinforcement Learning on Reward-Punishment Framework—0
Hyperbolic Deep Reinforcement Learning—0
Hyperbolic Embeddings for Learning Options in Hierarchical Reinforcement Learning—0
Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning—0
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem—0
Show:102550
← PrevPage 208 of 605Next →

Benchmark Results

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