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 3526–3550 of 15113 papers

TitleStatusHype
From Goal-Conditioned to Language-Conditioned Agents via Vision-Language Models—0
Energy Saving in 6G O-RAN Using DQN-based xApp—0
Physics Enhanced Residual Policy Learning (PERPL) for safety cruising in mixed traffic platooning under actuator and communication delay—0
A novel agent with formal goal-reaching guarantees: an experimental study with a mobile robot—0
CANDERE-COACH: Reinforcement Learning from Noisy Feedback—0
Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach—0
A Distribution-Aware Flow-Matching for Generating Unstructured Data for Few-Shot Reinforcement Learning—0
SoloParkour: Constrained Reinforcement Learning for Visual Locomotion from Privileged Experience—0
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling—0
OMG-RL:Offline Model-based Guided Reward Learning for Heparin Treatment—0
MAGICS: Adversarial RL with Minimax Actors Guided by Implicit Critic Stackelberg for Convergent Neural Synthesis of Robot Safety—0
TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning—0
Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL—0
Disentangling Recognition and Decision Regrets in Image-Based Reinforcement Learning—0
The Central Role of the Loss Function in Reinforcement Learning—0
Reinforcement Learning as an Improvement Heuristic for Real-World Production Scheduling—0
IMRL: Integrating Visual, Physical, Temporal, and Geometric Representations for Enhanced Food Acquisition—0
Data-Efficient Quadratic Q-Learning Using LMIs—0
An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Large-Scale Recommender Systems—0
On-policy Actor-Critic Reinforcement Learning for Multi-UAV Exploration—0
A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler—0
Robust Reinforcement Learning with Dynamic Distortion Risk MeasuresCode0
Instigating Cooperation among LLM Agents Using Adaptive Information Modulation—0
Mitigating Partial Observability in Adaptive Traffic Signal Control with Transformers—0
Offline Reinforcement Learning for Learning to Dispatch for Job Shop SchedulingCode0
Show:102550
← PrevPage 142 of 605Next →

Benchmark Results

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