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 5801–5825 of 15113 papers

TitleStatusHype
HyperNCA: Growing Developmental Networks with Neural Cellular AutomataCode1
Deep Reinforcement Learning-based Radio Resource Allocation and Beam Management under Location Uncertainty in 5G mmWave Networks—0
Graph Neural Network based Agent in Google Research Football—0
Finite-Time Analysis of Temporal Difference Learning: Discrete-Time Linear System Perspective—0
Reward Reports for Reinforcement LearningCode1
TASAC: a twin-actor reinforcement learning framework with stochastic policy for batch process control—0
Optimizing Nitrogen Management with Deep Reinforcement Learning and Crop Simulations—0
Learning how to Interact with a Complex Interface using Hierarchical Reinforcement Learning—0
6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement LearningCode1
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach—0
Resilient robot teams: a review integrating decentralised control, change-detection, and learning—0
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics—0
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency—0
Understanding and Preventing Capacity Loss in Reinforcement Learning—0
SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics—0
Reinforcement Learning with Intrinsic Affinity for Personalized Prosperity Management—0
Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning—0
A Reinforcement Learning-based Volt-VAR Control Dataset and Testing EnvironmentCode1
A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines—0
Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply ChainsCode1
Federated Learning for Distributed Energy-Efficient Resource Allocation—0
Network Topology Optimization via Deep Reinforcement Learning—0
When Is Partially Observable Reinforcement Learning Not Scary?—0
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction EstimationCode1
Optimizing Tensor Network Contraction Using Reinforcement Learning—0
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Benchmark Results

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