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

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Showing 3251–3300 of 15113 papers

TitleStatusHype
Dynamic Retail Pricing via Q-Learning -- A Reinforcement Learning Framework for Enhanced Revenue Management—0
LLM-Based Offline Learning for Embodied Agents via Consistency-Guided Reward Ensemble—0
Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards—0
PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement—0
Free^2Guide: Gradient-Free Path Integral Control for Enhancing Text-to-Video Generation with Large Vision-Language Models—0
Probing for Consciousness in Machines—0
M3: Mamba-assisted Multi-Circuit Optimization via MBRL with Effective Scheduling—0
Unsupervised Event Outlier Detection in Continuous Time—0
Reinforcement learning-enhanced genetic algorithm for wind farm layout optimization—0
From Laws to Motivation: Guiding Exploration through Law-Based Reasoning and Rewards—0
Broad Critic Deep Actor Reinforcement Learning for Continuous Control—0
Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration—0
Enhancing Molecular Design through Graph-based Topological Reinforcement Learning—0
Free Energy Projective Simulation (FEPS): Active inference with interpretability—0
Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward—0
Segmenting Action-Value Functions Over Time-Scales in SARSA via TD(Δ)—0
GraCo -- A Graph Composer for Integrated Circuits—0
Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problemsCode0
Model Checking for Reinforcement Learning in Autonomous Driving: One Can Do More Than You Think!—0
Time-Scale Separation in Q-Learning: Extending TD() for Action-Value Function Decomposition—0
A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedback—0
Provably Efficient Action-Manipulation Attack Against Continuous Reinforcement Learning—0
ACING: Actor-Critic for Instruction Learning in Black-Box Large Language ModelsCode0
Coarse-to-fine Q-Network with Action Sequence for Data-Efficient Robot Learning—0
GRL-Prompt: Towards Knowledge Graph based Prompt Optimization via Reinforcement Learning—0
Action-Attentive Deep Reinforcement Learning for Autonomous Alignment of BeamlinesCode0
Regret-Free Reinforcement Learning for LTL Specifications—0
No-regret Exploration in Shuffle Private Reinforcement Learning—0
Enhancing Decision Transformer with Diffusion-Based Trajectory Branch Generation—0
Robust Reinforcement Learning under Diffusion Models for Data with Jumps—0
Continual Task Learning through Adaptive Policy Self-CompositionCode0
Upside-Down Reinforcement Learning for More Interpretable Optimal Control—0
Preserving Expert-Level Privacy in Offline Reinforcement Learning—0
Robust Defense Against Extreme Grid Events Using Dual-Policy Reinforcement Learning Agents—0
Modulating Reservoir Dynamics via Reinforcement Learning for Efficient Robot Skill Synthesis—0
An Investigation of Offline Reinforcement Learning in Factorisable Action SpacesCode0
Financial News-Driven LLM Reinforcement Learning for Portfolio Management—0
Stable Continual Reinforcement Learning via Diffusion-based Trajectory Replay—0
Adaptive Learning of Design Strategies over Non-Hierarchical Multi-Fidelity Models via Policy Alignment—0
Multi-agent Path Finding for Timed Tasks using Evolutionary Games—0
Towards Sample-Efficiency and Generalization of Transfer and Inverse Reinforcement Learning: A Comprehensive Literature Review—0
Continual Adversarial Reinforcement Learning (CARL) of False Data Injection detection: forgetting and explainability—0
The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning—0
To bootstrap or to rollout? An optimal and adaptive interpolation—0
Innate-Values-driven Reinforcement Learning based Cognitive Modeling—0
Recommender systems and reinforcement learning for human-building interaction and context-aware support: A text mining-driven review of scientific literatureCode0
Towards Practical Deep Schedulers for Allocating Cellular Radio Resources—0
Robot See, Robot Do: Imitation Reward for Noisy Financial Environments—0
RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm—0
LLMStinger: Jailbreaking LLMs using RL fine-tuned LLMs—0
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Benchmark Results

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