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 6051–6075 of 15113 papers

TitleStatusHype
Snap Angle Prediction for 360° Panoramas—0
Snap Angle Prediction for 360^ Panoramas—0
SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning—0
SocialAI: Benchmarking Socio-Cognitive Abilities in Deep Reinforcement Learning Agents—0
Social diversity and social preferences in mixed-motive reinforcement learning—0
Social Interpretable Reinforcement Learning—0
Socially Fair Reinforcement Learning—0
Social Network Structure Shapes Innovation: Experience-sharing in RL with SAPIENS—0
Social Vehicle Swarms: A Novel Perspective on Social-aware Vehicular Communication Architecture—0
Socratic RL: A Novel Framework for Efficient Knowledge Acquisition through Iterative Reflection and Viewpoint Distillation—0
Soft Action Priors: Towards Robust Policy Transfer—0
Soft Actor-Critic With Integer Actions—0
SoftCTRL: Soft conservative KL-control of Transformer Reinforcement Learning for Autonomous Driving—0
Soft Decomposed Policy-Critic: Bridging the Gap for Effective Continuous Control with Discrete RL—0
Soft Expert Reward Learning for Vision-and-Language Navigation—0
Regularized Softmax Deep Multi-Agent Q-Learning—0
Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning—0
Soft policy optimization using dual-track advantage estimator—0
Soft Q-Learning with Mutual-Information Regularization—0
Soft-Robust Actor-Critic Policy-Gradient—0
Soft-Robust Algorithms for Batch Reinforcement Learning—0
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning—0
Solar Power driven EV Charging Optimization with Deep Reinforcement Learning—0
SOLD: Slot Object-Centric Latent Dynamics Models for Relational Manipulation Learning from Pixels—0
Solipsistic Reinforcement Learning—0
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Benchmark Results

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