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 9326–9350 of 15113 papers

TitleStatusHype
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Code1
Instance-based Generalization in Reinforcement Learning—0
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning—0
Learning Multi-Agent Communication through Structured Attentive ReasoningCode1
IV-Posterior: Inverse Value Estimation for Interpretable Policy Certificates—0
Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUpCode0
UniCon: Universal Neural Controller For Physics-based Character Motion—0
Soft-Robust Algorithms for Batch Reinforcement Learning—0
Optimizing the Neural Architecture of Reinforcement Learning AgentsCode0
Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems—0
Cluster Based Deep Contextual Reinforcement Learning for top-k Recommendations—0
Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems—0
Optimal Mixture Weights for Off-Policy Evaluation with Multiple Behavior Policies—0
Offline Reinforcement Learning Hands-On—0
Self-supervised Visual Reinforcement Learning with Object-centric RepresentationsCode1
Minimax Sample Complexity for Turn-based Stochastic Game—0
Human-Agent Cooperation in Bridge Bidding—0
Adaptable Automation with Modular Deep Reinforcement Learning and Policy Transfer—0
Deep Reinforcement Learning for Resource Constrained Multiclass Scheduling in Wireless Networks—0
A survey of benchmarking frameworks for reinforcement learning—0
Efficient Information Diffusion in Time-Varying Graphs through Deep Reinforcement LearningCode0
Real-time Active Vision for a Humanoid Soccer Robot Using Deep Reinforcement Learning—0
Reinforcement Learning-based Joint Path and Energy Optimization of Cellular-Connected Unmanned Aerial Vehicles—0
Optimization of the Model Predictive Control Update Interval Using Reinforcement LearningCode1
Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning—0
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Benchmark Results

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