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 2801–2825 of 15113 papers

TitleStatusHype
Sample-Efficient Reinforcement Learning of Koopman eNMPC—0
AED: Automatic Discovery of Effective and Diverse Vulnerabilities for Autonomous Driving Policy with Large Language Models—0
RLCAD: Reinforcement Learning Training Gym for Revolution Involved CAD Command Sequence Generation—0
Mining-Gym: A Configurable RL Benchmarking Environment for Truck Dispatch SchedulingCode0
Option Discovery Using LLM-guided Semantic Hierarchical Reinforcement Learning—0
Evolutionary Policy Optimization—0
Continual Reinforcement Learning for HVAC Systems Control: Integrating Hypernetworks and Transfer LearningCode0
Optimizing Navigation And Chemical Application in Precision Agriculture With Deep Reinforcement Learning And Conditional Action Tree—0
Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization—0
Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization—0
ViVa: Video-Trained Value Functions for Guiding Online RL from Diverse Data—0
A Roadmap Towards Improving Multi-Agent Reinforcement Learning With Causal Discovery And Inference—0
Transferable Latent-to-Latent Locomotion Policy for Efficient and Versatile Motion Control of Diverse Legged Robots—0
ComfyGPT: A Self-Optimizing Multi-Agent System for Comprehensive ComfyUI Workflow Generation—0
Autonomous Radiotherapy Treatment Planning Using DOLA: A Privacy-Preserving, LLM-Based Optimization Agent—0
Curriculum RL meets Monte Carlo Planning: Optimization of a Real World Container Management ProblemCode0
Causally Aligned Curriculum Learning—0
Reinforcement Learning-based Heuristics to Guide Domain-Independent Dynamic ProgrammingCode0
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models—0
Towards Automated Semantic Interpretability in Reinforcement Learning via Vision-Language Models—0
UAS Visual Navigation in Large and Unseen Environments via a Meta Agent—0
Grammar and Gameplay-aligned RL for Game Description Generation with LLMs—0
OThink-MR1: Stimulating multimodal generalized reasoning capabilities via dynamic reinforcement learning—0
Behaviour Discovery and Attribution for Explainable Reinforcement Learning—0
Reward Training Wheels: Adaptive Auxiliary Rewards for Robotics Reinforcement Learning—0
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Benchmark Results

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