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

Showing 44014450 of 15113 papers

TitleStatusHype
Solving Collaborative Dec-POMDPs with Deep Reinforcement Learning Heuristics0
Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement LearningCode0
Foundation Models for Semantic Novelty in Reinforcement Learning0
Leveraging Sequentiality in Reinforcement Learning from a Single DemonstrationCode0
Leveraging Offline Data in Online Reinforcement Learning0
Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information0
Doubly Inhomogeneous Reinforcement LearningCode0
Efficient Compressed Ratio Estimation Using Online Sequential Learning for Edge Computing0
Learning to Follow Instructions in Text-Based GamesCode0
Pretraining in Deep Reinforcement Learning: A Survey0
Reinforcement Learning with Stepwise Fairness Constraints0
Progress and summary of reinforcement learning on energy management of MPS-EV0
Reward-Predictive Clustering0
Curriculum-based Asymmetric Multi-task Reinforcement LearningCode1
FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement LearningCode6
Wall Street Tree Search: Risk-Aware Planning for Offline Reinforcement Learning0
Spatio-temporal Incentives Optimization for Ride-hailing Services with Offline Deep Reinforcement Learning0
ProtoX: Explaining a Reinforcement Learning Agent via PrototypingCode0
Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain0
Design Process is a Reinforcement Learning ProblemCode1
Decentralized Federated Reinforcement Learning for User-Centric Dynamic TFDD Control0
De novo PROTAC design using graph-based deep generative modelsCode1
Diversity-based Deep Reinforcement Learning Towards Multidimensional Difficulty for Fighting Game AICode0
The Benefits of Model-Based Generalization in Reinforcement LearningCode0
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for RoboticsCode1
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning0
Synthesis of separation processes with reinforcement learningCode1
A Survey on Reinforcement Learning in Aviation Applications0
Learning safety in model-based Reinforcement Learning using MPC and Gaussian ProcessesCode1
Contrastive Value Learning: Implicit Models for Simple Offline RL0
lilGym: Natural Language Visual Reasoning with Reinforcement Learning0
Leveraging Fully Observable Policies for Learning under Partial ObservabilityCode0
GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond0
Sensor Control for Information Gain in Dynamic, Sparse and Partially Observed Environments0
Reinforcement Learning in Non-Markovian Environments0
Oracle Inequalities for Model Selection in Offline Reinforcement Learning0
Scalable Multi-Agent Reinforcement Learning through Intelligent Information AggregationCode1
Theta-Resonance: A Single-Step Reinforcement Learning Method for Design Space Exploration0
Deep Reinforcement Learning for IRS Phase Shift Design in Spatiotemporally Correlated Environments0
Causal Counterfactuals for Improving the Robustness of Reinforcement LearningCode1
Wind Power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach0
Over-communicate no more: Situated RL agents learn concise communication protocols0
Spatial-temporal recurrent reinforcement learning for autonomous shipsCode1
Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints0
Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network0
Dual Generator Offline Reinforcement Learning0
Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systems0
Learning to Grasp the Ungraspable with Emergent Extrinsic Dexterity0
Behavior Prior Representation learning for Offline Reinforcement LearningCode0
DynamicLight: Two-Stage Dynamic Traffic Signal TimingCode0
Show:102550
← PrevPage 89 of 303Next →

Benchmark Results

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