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 751–800 of 15113 papers

TitleStatusHype
CTSAC: Curriculum-Based Transformer Soft Actor-Critic for Goal-Oriented Robot Exploration—0
Pauli Network Circuit Synthesis with Reinforcement Learning—0
Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical InvestigationCode1
Synchronous vs Asynchronous Reinforcement Learning in a Real World Robot—0
APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional games—0
A Reinforcement Learning-Driven Transformer GAN for Molecular Generation—0
FLEX: A Framework for Learning Robot-Agnostic Force-based Skills Involving Sustained Contact Object Manipulation—0
Dynamic Angle Selection in X-Ray CT: A Reinforcement Learning Approach to Optimal Stopping—0
TERL: Large-Scale Multi-Target Encirclement Using Transformer-Enhanced Reinforcement LearningCode1
Evaluation-Time Policy Switching for Offline Reinforcement Learning—0
Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse RewardsCode2
Sketch-to-Skill: Bootstrapping Robot Learning with Human Drawn Trajectory Sketches—0
Adaptive Torque Control of Exoskeletons under Spasticity Conditions via Reinforcement Learning—0
Learning to reset in target search problemsCode0
Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question AnsweringCode3
Dynamic Obstacle Avoidance with Bounded Rationality Adversarial Reinforcement Learning—0
Exploring Competitive and Collusive Behaviors in Algorithmic Pricing with Deep Reinforcement Learning—0
Reinforcement Learning-Based Controlled Switching Approach for Inrush Current Minimization in Power Transformers—0
Scalable Evaluation of Online Facilitation Strategies via Synthetic Simulation of DiscussionsCode0
Representation-based Reward Modeling for Efficient Safety Alignment of Large Language Model—0
SortingEnv: An Extendable RL-Environment for an Industrial Sorting Process—0
Safe Continual Domain Adaptation after Sim2Real Transfer of Reinforcement Learning Policies in Robotics—0
SySLLM: Generating Synthesized Policy Summaries for Reinforcement Learning Agents Using Large Language Models—0
H2-MARL: Multi-Agent Reinforcement Learning for Pareto Optimality in Hospital Capacity Strain and Human Mobility during Epidemic—0
DeepSeek-Inspired Exploration of RL-based LLMs and Synergy with Wireless Networks: A Survey—0
NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models—0
Solving Bayesian inverse problems with diffusion priors and off-policy RL—0
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningCode7
Optimisation of the Accelerator Control by Reinforcement Learning: A Simulation-Based Approach—0
Local Look-Ahead Guidance via Verifier-in-the-Loop for Automated Theorem Proving—0
Edge AI-Powered Real-Time Decision-Making for Autonomous Vehicles in Adverse Weather Conditions—0
Large-scale Regional Traffic Signal Control Based on Single-Agent Reinforcement Learning—0
Unified Locomotion Transformer with Simultaneous Sim-to-Real Transfer for Quadrupeds—0
MarineGym: A High-Performance Reinforcement Learning Platform for Underwater Robotics—0
Evaluating Reinforcement Learning Safety and Trustworthiness in Cyber-Physical Systems—0
Balancing SoC in Battery Cells using Safe Action Perturbations—0
In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents—0
Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning—0
Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Model—0
A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models—0
Zero-Shot Action Generalization with Limited Observations—0
HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents—0
V-Max: A Reinforcement Learning Framework for Autonomous DrivingCode2
Regulatory DNA sequence Design with Reinforcement LearningCode1
MoRE: Unlocking Scalability in Reinforcement Learning for Quadruped Vision-Language-Action Models—0
Adaptive routing protocols for determining optimal paths in AI multi-agent systems: a priority- and learning-enhanced approach—0
Efficient Neural Clause-Selection Reinforcement—0
LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RLCode4
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning—0
VisRL: Intention-Driven Visual Perception via Reinforced ReasoningCode1
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Benchmark Results

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