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 4351–4375 of 15113 papers

TitleStatusHype
UNEX-RL: Reinforcing Long-Term Rewards in Multi-Stage Recommender Systems with UNidirectional EXecution—0
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization—0
Parrot: Pareto-optimal Multi-Reward Reinforcement Learning Framework for Text-to-Image Generation—0
Model-Free Reinforcement Learning for Automated Fluid Administration in Critical Care—0
The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed RewardsCode0
Reinforcement Learning for Optimizing RAG for Domain Chatbots—0
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces—0
An Information Theoretic Approach to Interaction-Grounded Learning—0
Innate-Values-driven Reinforcement Learning based Cooperative Multi-Agent Cognitive Modeling—0
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments—0
Using reinforcement learning to improve drone-based inference of greenhouse gas fluxesCode0
Behavioural Cloning in VizDoom—0
Long-term Safe Reinforcement Learning with Binary Feedback—0
Deep Reinforcement Learning for Multi-Truck Vehicle Routing Problems with Multi-Leg Demand Routes—0
NovelGym: A Flexible Ecosystem for Hybrid Planning and Learning Agents Designed for Open Worlds—0
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond—0
Synergistic Formulaic Alpha Generation for Quantitative Trading based on Reinforcement Learning—0
Adaptive Discounting of Training Time Attacks—0
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty—0
A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement LearningCode0
A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management—0
Towards an Adaptable and Generalizable Optimization Engine in Decision and Control: A Meta Reinforcement Learning Approach—0
GLIDE-RL: Grounded Language Instruction through DEmonstration in RL—0
Improving Unsupervised Hierarchical Representation with Reinforcement LearningCode0
Data Assimilation in Chaotic Systems Using Deep Reinforcement LearningCode0
Show:102550
← PrevPage 175 of 605Next →

Benchmark Results

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